Search results for: economic planning optimization

Authors: Paul Saah, Charles Mbohwa, Nelson Sizwe Madonsela

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In the context of developing countries, this study explores a crucial component of economic development by examining the reasons behind the failure of small and medium-sized enterprises (SMEs). SMEs are acknowledged as essential drivers of economic expansion, job creation, and poverty alleviation in emerging countries. This research uses South Africa as a case study to evaluate the reasons why SMEs fail in developing nations. This study explores a quantitative research methodology to investigate the complex causes of SME failures using statistical tools and reliability tests. To ensure the viability of data collection, a sample size of 400 small business owners was chosen using a non-probability selection technique. A closed-ended questionnaire was the primary technique used to obtain detailed information from the participants. Data was analysed and interpreted using computer software packages such as the Statistical Package for the Social Sciences (SPSS). According to the findings, the main reasons why SMEs fail in developing nations are a lack of strategic business planning, a lack of funding, poor management, a lack of innovation, a lack of business research and a low level of education and training. The results of this study show that SMEs can be sustainable and successful as long as they comprehend and use the suggested small business success determining variables into their daily operations. This implies that the more SMEs in developing countries implement the proposed determinant factors of small business success in their business operations the more the businesses are likely to succeed and vice versa.

Keywords: failure, developing countries, SMEs, economic development, South Africa

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Authors: Elizelle Juanee Cilliers

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Recent planning thinking has laid the foundations for a general sense of best practice that aims to enhance the quality of life, suggesting an open and participatory process. It is accepted that integration of top-down and bottom-up approaches may lead to efficient action in environments and sustainable planning and development, although it is also accepted that such an integrated approach has various challenges of implementation. A flexible framework in which the strengths of both the top-down and bottom-up approaches were explored in this research, based on the EU Interreg VALUE Added project and five case studies where student education and student involvement played a crucial role within the participation process of the redesign of the urban environment. It was found that international student workshops were an effective tool to integrate bottom-up and top-down structures, as it acted as catalyst for communication, interaction, creative design, quick transformation from planning to implementation, building social cohesion, finding mutual ground between stakeholders and thus enhancing overall quality of life and quality of environments. It offered a good alternative to traditional participation modes and created a platform for an integrative planning approach. The role and importance of education and integration within the urban environment were emphasized.

Keywords: top-down, bottom-up, flexible, student involvement

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Authors: Olifan Degebas Olkeba

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Background: Males participate in family planning by utilizing the method, having discussions, approving decisions, and supporting their partners and other family members. One of the reasons Ethiopia has a low rate of FP use is the poor participation of men in family planning. So, the finding of the study could help married men and other stakeholders to alleviate the problems related to low involvement. Objective: To assess males’ involvement in family planning use and associated factors among married men in the pastoralist community of Yabelo district, Borena, Oromia, Ethiopia, 2024. Methods: Cross sectional study design supplemented by qualitative and multistage sampling method for quantitative one and purposive sampling method for qualitative was done. The interviewer administered questionnaires from 531 samples for quantitative and from 14 key informants for qualitative were taken. Quantitative data were entered using Epi Info version 7.2.2.6 and analyzed using SPSS version 24. Bivariate associations between dependent and independent variables were examined. Multi variable logistic regression analysis was done to identify factors significantly associated with male involvement. Qualitative data was analyzed using open code 4.03. The study was conducted from January 1-February 29, 2024. Results: A total of 531 respondents participated. The mean age of the study participant was 28 ±2.1 (SD). The prevalence of male involvement in FP use among married males in Yabelo district was 9.6 (AOR= 9.6, 95% CI: 7.14-12.15). Age above 40 years (AOR=0.18, 95% CI: 0.05-0.6 p=0.009), educational status unable read and write (AOR=9.4, 95% CI:3.5-25.4 p=0.001), read and write only (AOR=7.1, 95% CI:2.4-21.4 p=0.001), knowledge on side effects of FP (AOR=2.35, 95% CI: 1.09-5.06 p=0.029) were factors associated with male involvement in FP use. A total of 14 key informants participated in the interview of qualitative part and culturally perceived FP issues, lack of awareness and desire of more children were among the reasons for low involvement in FP use. Conclusion: The finding of the study showed that the magnitude of male involvement in family planning use was low. Age (>40), educational status (read and write only) and fear of side effects were factors associated with low husband involvement in FP use. Therefore, family planning programs need to target men at all levels of the service.

Keywords: family planning, male involvement, married men, Yabelo district

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Authors: Javed Mohammed

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As urbanization process has been and will be happening in an unprecedented scale worldwide, strong requirements from academic research and practical fields for smart management and intelligent planning of cities are pressing to handle increasing demands of infrastructure and potential risks of inhabitants agglomeration in disaster management. Geo-spatial data and Geographic Information System (GIS) are essential components for building smart cities in a basic way that maps the physical world into virtual environment as a referencing framework. On higher level, GIS has been becoming very important in smart cities on different sectors. In the digital city era, digital maps and geospatial databases have long been integrated in workflows in land management, urban planning and transportation in government. People have anticipated GIS to be more powerful not only as an archival and data management tool but also as spatial models for supporting decision-making in intelligent cities. The purpose of this project is to offer observations and analysis based on a detailed discussion of Geographic Information Systems( GIS) driven Framework towards the development of Smart and Sustainable Cities through high penetration of Renewable Energy Technologies.

Keywords: digital maps, geo-spatial, geographic information system, smart cities, renewable energy, urban planning

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Authors: Mariyam Arif, Ye Liu, Israr Ul Haq, Ahsan Ashfaq

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High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.

Keywords: artificial neural networks, demand-side management, economic dispatch, linear programming, power generation dispatch

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Authors: Fernando Augusto Ullmann Tobe, Moacyr Amaral Domingues, Figueiredo, Stephany Rie Yamamoto Gushiken

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The purpose of this paper is to present the process of elaborating the layout of an assembly line of a welding industry using the principles of lean manufacturing as the main driver. The objective of this paper is relevant since the current layout of the assembly line causes non-productive times for operators, being related to the lean waste of unnecessary movements. The methodology used for the project development was Project-based Learning (PBL), which is an active way of learning focused on real problems. The process of selecting the methodology for layout planning was developed considering three criteria to evaluate the most relevant one for this paper's goal. As a result of this evaluation, Systematic Layout Planning was selected, and three steps were added to it – Value Stream Mapping for the current situation and after layout changed and the definition of lean tools and layout type. This inclusion was to consider lean manufacturing in the layout redesign of the industry. The layout change resulted in an increase in the value-adding time of operations carried out in the sector, reduction in movement times between previous and final assemblies, and in cost savings regarding the man-hour value of the employees, which can be invested in productive hours instead of movement times.

Keywords: assembly line, layout, lean manufacturing, systematic layout planning

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Authors: Umar Hayat, Shahid Ali, Lala Rukh

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Foreign aid is one of the critical variables that promote economic growth. This paper is an attempt to examine the long-run relationship between foreign aid and economic growth for Pakistan over the period of 1972 to 2021. This study uses Johnson's co-integration technique to investigate the long-run relationship among the variables in the model. For short-run dynamics, we utilized the Error Correction Mechanism (ECM). The results strongly support the conventional view about aid-led growth. The analysis of the impact of aid on growth both at the micro and the macro levels generally gives different results. The result shows that in the short run inference of foreign aid under the nondemocratic form of government is significant negatively, while foreign aid does not affect economic growth in the case of democratic government.

Keywords: foreign aid, economic growth, political regimes, developing economy

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Authors: Nadezhda Nikolaeva, Tatyana Alexandrova, Alexandr Alexandrov

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Processing of high-silicon bauxite on the base of the traditional clinkering method is related to high power consumption and capital investments, which makes production of alumina from those ores non-competitive in terms of basic economic showings. For these reasons, development of technological solutions enabling to process bauxites with various chemical and mineralogical structures efficiently with low level of thermal power consumption is important. Flow sheet of the studies on washability of ores from the Timanskoe and the Severo-Onezhskoe deposits is on the base of the flotation method.

Keywords: low-quality bauxite, resource-saving technology, optimization, aluminum, conditioning of composition, separation characteristics

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of CSC modeling accommodates conceptual or process models which discuss general management frameworks and do not relate to acknowledged soft OR methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, mathematical formulation, structure, objectives, solution approach, software used and decision level. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop robust mathematical optimization models for the CSC. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without the consequential reform of generic concepts to match the unique characteristics of the construction industry.

Keywords: construction supply chain management, modeling, operations research, optimization, simulation

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Emily Kambalame

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Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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Authors: A. Chatel, I. S. Torreguitart, T. Verstraete

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The paper deals with a single point optimization of the LS89 turbine using an adjoint optimization and defining the design variables within a CAD system. The advantage of including the CAD model in the design system is that higher level constraints can be imposed on the shape, allowing the optimized model or component to be manufactured. However, CAD-based approaches restrict the design space compared to node-based approaches where every node is free to move. In order to preserve a rich design space, we develop a methodology to refine the CAD model during the optimization and to create the best parameterization to use at each time. This study presents a methodology to progressively refine the design space, which combines parametric effectiveness with a differential evolutionary algorithm in order to create an optimal parameterization. In this manuscript, we show that by doing the parameterization at the CAD level, we can impose higher level constraints on the shape, such as the axial chord length, the trailing edge radius and G2 geometric continuity between the suction side and pressure side at the leading edge. Additionally, the adjoint sensitivities are filtered out and only smooth shapes are produced during the optimization process. The use of algorithmic differentiation for the CAD kernel and grid generator allows computing the grid sensitivities to machine accuracy and avoid the limited arithmetic precision and the truncation error of finite differences. Then, the parametric effectiveness is computed to rate the ability of a set of CAD design parameters to produce the design shape change dictated by the adjoint sensitivities. During the optimization process, the design space is progressively enlarged using the knot insertion algorithm which allows introducing new control points whilst preserving the initial shape. The position of the inserted knots is generally assumed. However, this assumption can hinder the creation of better parameterizations that would allow producing more localized shape changes where the adjoint sensitivities dictate. To address this, we propose using a differential evolutionary algorithm to maximize the parametric effectiveness by optimizing the location of the inserted knots. This allows the optimizer to gradually explore larger design spaces and to use an optimal CAD-based parameterization during the course of the optimization. The method is tested on the LS89 turbine cascade and large aerodynamic improvements in the entropy generation are achieved whilst keeping the exit flow angle fixed. The trailing edge and axial chord length, which are kept fixed as manufacturing constraints. The optimization results show that the multilevel optimizations were more efficient than the single level optimization, even though they used the same number of design variables at the end of the multilevel optimizations. Furthermore, the multilevel optimization where the parameterization is created using the optimal knot positions results in a more efficient strategy to reach a better optimum than the multilevel optimization where the position of the knots is arbitrarily assumed.

Keywords: adjoint, CAD, knots, multilevel, optimization, parametric effectiveness

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Authors: Masilonyane Mokhele

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Across the world, different planning models of the so-called airport-led developments are becoming bandwagons hailed as key to the future of cities. However, in the existing knowledge, there is paucity of empirically informed description and explanation of the economic fundamentals driving the forces of attraction of airports. This void is arguably a result of the absence of an appropriate theoretical framework to guide the analyses. Given this paucity, the aim of the paper is to contribute towards a theoretical framework that could be used to describe and explain forces that drive the location and mix of airport-centric developments. Towards achieving this aim, the objectives of the paper are: one, to establish the type of economic activities that are located on and around O.R. Tambo International Airport (ORTIA), and analyse the reasons for locating there; two, to establish changes that have occurred over time in the form of the airport-centric development of ORTIA; three, to identify the propulsive economic qualities of ORTIA; four, to analyse the spatial, economic and structural linkages within the airport-centric development of ORTIA, between the airport-centric development and the airport, as well as the airport-centric development’s linkages with their metropolitan area and other regional, national and international airport-centric developments and locations. To address the objectives above, the study adopted a case study approach, centred on ORTIA in South Africa: Africa’s busiest airport in terms of passengers and airfreight handled. Using a lens of location theory, a survey was adopted as a main research method, wherein telephonic interviews were conducted with a representative number of firms on and around ORTIA. Other data collection methods encompassed in-depth qualitative interviews (to augment the information obtained through the survey) and analysis of secondary information, particularly as regards establishing changes that have occurred in the form of ORTIA and surrounds. From the empirical findings, ORTIA was discovered to have propulsive economic qualities that act as significant forces of attraction in the clustering of firms. Together with its airport-centric development, ORTIA was discovered to have growth pole properties because of the linkages that occur within the study area, and the linkages that exist between the airport-centric firms and the airport. It was noted that the transport-oriented firms (typified by couriers and freight carriers) act as anchors in some fellow airport-centric firms making use of elements of urbanisation economies, particularly as regards the use of the airport for airfreight services. The empirical findings presented in the paper (in conjunction with results from other airport-centric development case studies) could be used as contribution towards extending theory that describes and explains forces that drive the location and mix of airport-centric developments.

Keywords: airports, airport-centric development, O. R. Tambo international airport, South Africa

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Authors: Helia Moayedi, Mahdi Moaidi

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Nowadays, the managing and planning of hospitals is facing many problems. Failure to recognize the main criteria for strategic management to ensure long-term hospital performance can lead to many health problems. To achieve this goal, a qualitative-quantitate method titled Delphi-Fuzzy has been applied. This strategy makes it possible for experts to screen among the most important criteria in strategic management. To conduct this operation, a statistical society consisting of 20 experts in Ahwaz hospitals has been questioned. The final model confirms the key criterions after three stages of Delphi. This model provides the possibility to focus on the basic criteria and can determine the organization’s main orientation.

Keywords: Delphi-fuzzy method, hospital management, long-term planning, qualitative-quantitate method, screening of strategic criteria, strategic planning

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Authors: To Quyen Le, Oswald Devisch, Tu Anh Trinh, Els Hannes

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Urban centres worldwide are affected differently by flooding. In Vietnam this impact is increasingly negative caused by a process of rapid urbanisation. Traditional spatial planning and flood mitigation planning are not able to deal with this growing threat. This article therefore proposes to focus on increasing the participation of local communities in flood control and management. It explores, on the basis of a design studio exercise, how lay knowledge on flooding can be integrated within planning processes. The article presents a theoretical basis for the structured criterion for site selection for a flood resilient urban park from the perspective of science, then discloses the tacit and explicit knowledge of the flood-prone area and finally integrates this knowledge into the design strategies for flood resilient urban park design.

Keywords: analytic hierarchy process, AHP, design resilience, flood resilient urban park, knowledge integration

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Authors: Mehran Barani Shikhrobat, Roger Flanagan

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The construction planning and scheduling based on using the current tools and techniques is resulted deterministic in nature (Gantt chart, CPM) or applying a very little probability of completion (PERT) for each task. However, every project embodies assumptions and influences and should start with a complete set of clearly defined goals and constraints that remain constant throughout the duration of the project. Construction planners continue to apply the traditional methods and tools of “hard” project management that were developed for “ideal projects,” neglecting the potential influence of complexity on the design and construction process. The aim of this research is to investigate the emergence and growth of complexity in project planning and to provide a model to consider the influence of complexity on the total project duration at the post-contract award pre-construction stage of a project. The literature review showed that complexity originates from different sources of environment, technical, and workflow interactions. They can be divided into two categories of complexity factors, first, project tasks, and second, project organisation management. Project tasks may originate from performance, lack of resources, or environmental changes for a specific task. Complexity factors that relate to organisation and management refer to workflow and interdependence of different parts. The literature review highlighted the ineffectiveness of traditional tools and techniques in planning for complexity. However, this research focus on understanding the fundamental causes of the complexity of construction projects were investigated through a questionnaire with industry experts. The results were used to develop a model that considers the core complexity factors and their interactions. System dynamics were used to investigate the model to consider the influence of complexity on project planning. Feedback from experts revealed 20 major complexity factors that impact project planning. The factors are divided into five categories known as core complexity factors. To understand the weight of each factor in comparison, the Analytical Hierarchy Process (AHP) analysis method is used. The comparison showed that externalities are ranked as the biggest influence across the complexity factors. The research underlines that there are many internal and external factors that impact project activities and the project overall. This research shows the importance of considering the influence of complexity on the project master plan undertaken at the post-contract award pre-construction phase of a project.

Keywords: project planning, project complexity measurement, planning uncertainty management, project risk management, strategic project scheduling

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Stanley Mburu

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Maintenance performance measurement (MPM) represents an integrated aspect that considers both operational and maintenance related aspects while evaluating the effectiveness and efficiency of maintenance to ensure assets are working as they should. Three salient issues require to be addressed for an asset-intensive organization to employ an MPM-based framework to optimize maintenance. Firstly, the organization should establish important perfomance metric(s), in this case the maintenance objective(s), which they will be focuss on. The second issue entails aligning the maintenance objective(s) with maintenance optimization. This is achieved by deriving maintenance performance indicators that subsequently form an objective function for the optimization program. Lastly, the objective function is employed in an optimization program to derive maintenance decision support. In this study, we develop a framework that initially identifies the crucial maintenance performance measures, and employs them to derive maintenance decision support. The proposed framework is demonstrated in a case study of a geothermal drilling rig, where the objective function is evaluated utilizing a simulation-based model whose parameters are derived from empirical maintenance data. Availability, reliability and maintenance inventory are depicted as essential objectives requiring further attention. A simulation model is developed mimicking a drilling rig operations and maintenance where the sub-systems are modelled undergoing imperfect maintenance, corrective (CM) and preventive (PM), with the total cost as the primary performance measurement. Moreover, three maintenance spare inventory policies are considered; classical (retaining stocks for a contractual period), vendor-managed inventory with consignment stock and periodic monitoring order-to-stock (s, S) policy. Optimization results infer that the adoption of (s, S) inventory policy, increased PM interval and reduced reliance of CM actions offers improved availability and total costs reduction.

Keywords: maintenance, vendor-managed, decision support, performance, optimization

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Amanda Grace Ahl, Matthew Brummer

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‘Smart cities’ are not always as ‘smart’ as the term suggests, which is not often covered in the associated academic and public policy literatures. In what has become known as the smart city approach to urban planning, governments around the world are seeking to harness the power of information and communications technology with increasingly advanced data analytics to address major social, economic, and environmental issues reshaping the ways people live. The definitional and theoretical boundaries of the smart city framework are broad and at times ambiguous, as is empirical treatment of the topic. However, and for all the disparity, in investigating any number of institutional and policy prescriptions to the challenges faced by current and emerging metropoles, scholarly thought has hinged overwhelmingly on value-positive conceptions of informatics-centered design. From enhanced quality of services, to increased efficiency of resources, to improved communication between societal stakeholders, the smart city design is championed as a technological wellspring capable of providing answers to the systemic issues stymying a utopian image of the city. However, it is argued that this ‘techtopia’, has resulted in myopia within the discipline as to value-negative implications of such planning, such as weaknesses in practicality, scalability, social equity and affordability of solutions. In order to more carefully examine this observation - that ‘stupid’ represents an omitted variable bias in the study of ‘smart’ - this paper reviews critical cases of unsuccessful smart city developments. It is argued that also understanding the negative factors affiliated with the development processes is imperative for the advancement of theoretical foundations, policies, and strategies to further the smart city as an equitable, holistic urban innovation. What emerges from the process-tracing carried out in this study are distinctly negative lessons of smart city projects, the significance of which are vital for understanding how best to conceive smart urban planning in the 21st century.

Keywords: case study, city management, innovation system, negative lessons, smart city development

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Authors: Torsten Schwan, Rene Unger

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Simulation of thermal and electrical building performance more and more becomes part of an integrative planning process. Increasing requirements on energy efficiency, the integration of volatile renewable energy, smart control and storage management often cause tremendous challenges for building engineers and architects. This mainly affects commercial or non-residential buildings. Their energy consumption characteristics significantly distinguish from residential ones. This work focuses on the many-objective optimization problem indoor air quality and comfort, especially in non-residential buildings. Based on a brief description of intermediate dependencies between different requirements on indoor air treatment it extends existing Modelica-based building physics models with additional system states to adequately represent indoor air conditions. Interfaces to corresponding HVAC (heating, ventilation, and air conditioning) system and control models enable closed-loop analyzes of occupants' requirements and energy efficiency as well as profitableness aspects. A complex application scenario of a nearly-zero-energy school building shows advantages of presented evaluation process for engineers and architects. This way, clear identification of air quality requirements in individual rooms together with realistic model-based description of occupants' behavior helps to optimize HVAC system already in early design stages. Building planning processes can be highly improved and accelerated by increasing integration of advanced simulation methods. Those methods mainly provide suitable answers on engineers' and architects' questions regarding more exuberant and complex variety of suitable energy supply solutions.

Keywords: indoor air quality, dynamic simulation, energy efficient control, non-residential buildings

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Authors: Lydia Novozhilova, Vladimir Urazhdin

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An optimization problem for reinforced thin-walled vessels under uniform external pressure is considered. The conventional approaches to optimization generally start with pre-defined geometric parameters of the vessels, and then employ analytic or numeric calculations and/or experimental testing to verify functionality, such as stability under the projected conditions. The proposed approach consists of two steps. First, the feasibility domain will be identified in the multidimensional parameter space. Every point in the feasibility domain defines a design satisfying both geometric and functional constraints. Second, an objective function defined in this domain is formulated and optimized. The broader applicability of the suggested methodology is maximized by implementing the Support Vector Machines (SVM) classification algorithm of machine learning for identification of the feasible design region. Training data for SVM classifier is obtained using the Simulation package of SOLIDWORKS®. Based on the data, the SVM algorithm produces a curvilinear boundary separating admissible and not admissible sets of design parameters with maximal margins. Then optimization of the vessel parameters in the feasibility domain is performed using the standard algorithms for the constrained optimization. As an example, optimization of a ring-stiffened closed cylindrical thin-walled vessel with semi-spherical caps under high external pressure is implemented. As a functional constraint, von Mises stress criterion is used but any other stability constraint admitting mathematical formulation can be incorporated into the proposed approach. Suggested methodology has a good potential for reducing design time for finding optimal parameters of thin-walled vessels under uniform external pressure.

Keywords: design parameters, feasibility domain, von Mises stress criterion, Support Vector Machine (SVM) classifier

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Authors: Touil Djamal, Fergani Zineb

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In this study, an Organic Rankine Cycle (ORC) with Cyclohexane working fluid is proposed for cogeneration in the cement industry. In this regard: first, a parametric study is conducted to evaluate the effects of some key parameters on the system performances. Next, single and multi-objective optimizations are performed to achieve the system optimal design. The optimization considers the exergy efficiency, the cost per exergy unit and the environmental impact of the net produced power as objective functions. Finally, exergy, exergoeconomic and exergoenvironmental analysis of the cycle is carried out at the optimum operating conditions. The results show that the turbine inlet pressure, the pinch point temperature difference and the heat transfer fluid temperature have significant effects on the performances of the ORC system.

Keywords: organic rankine cycle, multi-objective optimization, exergy, exergoeconomic, exergoenvironmental, multi-objective optimisation, organic rankine cycle, cement plant

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Authors: Muhammad Abdul Qyyum, Kinza Qadeer, Moonyong Lee

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Globally, liquefied natural gas (LNG) has drawn interest as a green energy source in comparison with other fossil fuels, mainly because of its ease of transport and low carbon dioxide emissions. It is expected that demand for LNG will grow steadily over the next few decades. In addition, because the demand for clean energy is increasing, LNG production facilities are expanding into new natural gas reserves across the globe. However, LNG production is an energy and cost intensive process because of the huge power requirements for compression and refrigeration. Therefore, one of the major challenges in the LNG industry is to improve the energy efficiency of existing LNG processes through economic and ecological strategies. The advancement in expansion devices such as two-phase cryogenic expander (TPE) and cryogenic hydraulic turbine (HT) were exploited for energy and cost benefits in natural gas liquefaction. Retrofitting the conventional Joule–Thompson (JT) valve with TPE and HT have the potential to improve the energy efficiency of LNG processes. This research investigated the potential feasibility of the retrofitting of a dual mixed refrigerant (DMR) process by replacing the isenthalpic expansion with isentropic expansion corresponding to energy efficient LNG production. To fully take the potential benefit of the proposed process retrofitting, the proposed DMR schemes were optimized by using a Coggins optimization approach, which was implemented in Microsoft Visual Studio (MVS) environment and linked to the rigorous HYSYS® model. The results showed that the required energy of the proposed isentropic expansion based DMR process could be saved up to 26.5% in comparison with the conventional isenthalpic based DMR process using the JT valves. Utilization of the recovered energy into boosting the natural gas feed pressure could further improve the energy efficiency of the LNG process up to 34% as compared to the base case. This work will help the process engineers to overcome the challenges relating to energy efficiency and safety concerns of LNG processes. Furthermore, the proposed retrofitting scheme can also be implemented to improve the energy efficiency of other isenthalpic expansion based energy intensive cryogenic processes.

Keywords: cryogenic liquid turbine, Coggins optimization, dual mixed refrigerant, energy efficient LNG process, two-phase expander

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Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

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This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

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Authors: Hakim T. Kadhim, Faris A. Jabbar, Aldo Rona, Audrius Bagdanaviciu

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Computer-based optimization techniques can be employed to improve the efficiency of energy conversions processes, including reducing the aerodynamic loss in a thermal power plant turbomachine. In this paper, towards mitigating secondary flow losses, a design optimization workflow is implemented for the casing geometry of a 1.5 stage axial flow turbine that improves the turbine isentropic efficiency. The improved turbine is used in an open thermodynamic gas cycle with regeneration and cogeneration. Performance estimates are obtained by the commercial software Cycle – Tempo. Design and off design conditions are considered as well as variations in inlet air temperature. Reductions in both the natural gas specific fuel consumption and in CO₂ emissions are predicted by using the gas turbine cycle fitted with the new casing design. These gains are attractive towards enhancing the competitiveness and reducing the environmental impact of thermal power plant.

Keywords: axial flow turbine, computational fluid dynamics, gas turbine power plant, optimization

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Authors: Ntachobazi bosco

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Tourism Development and Planning in Rwanda: Rwanda, a small landlocked country located in the heart of Africa, has experienced significant growth in its tourism industry in recent years. The country’s stunning natural beauty, rich cultural heritage, and warm hospitality have made it an attractive destination for travelers from around the world. However, to ensure sustainable tourism development and planning, the Rwandan government has implemented various strategies and policies to promote responsible tourism practices. Infrastructure Development: To support the growth of the tourism industry, the Rwandan government has invested heavily in infrastructure development. This includes the construction of new hotels, resorts, and lodges, as well as the upgrading of existing facilities. The government has also improved the country’s transportation network, including the construction of new airports and the upgrading of existing ones. Conservation Efforts: Rwanda is home to several national parks and reserves, including the famous Volcanoes National Park, which is known for its mountain gorilla populations. To protect these natural wonders, the Rwandan government has implemented conservation efforts, such as the establishment of protected areas and the development of sustainable tourism practices. Community-Based Tourism: Community-based tourism is a key component of Rwanda’s tourism development strategy. The government has established several community-based tourism programs, which aim to involve local communities in the tourism industry and provide them with economic benefits. These programs include homestays, village tours, and cultural performances. Sustainable Tourism Practices: To promote sustainable tourism practices, the Rwandan government has implemented several initiatives, such as the use of eco-friendly accommodations and the promotion of responsible wildlife viewing practices. The government has also established the Rwanda Tourism Board, which is responsible for promoting and regulating the tourism industry. Challenges and Opportunities: Despite the growth of the tourism industry in Rwanda, several challenges need to be addressed, such as the lack of skilled labor and the need for more infrastructure development. However, there are also several opportunities for the industry, such as the potential for ecotourism and the growth of the meetings, incentives, conventions, and exhibitions (MICE) market.

Keywords: tourism, in rwanda, developent, in africa

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Authors: Muwaffaq Usman Adam, Isaac Quaye, Jim Anbazu, Yetimoni Kpeebi, Michael Osei-Assibey

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Urban informality, characterized by spontaneous and self-organized practices, plays a significant but often overlooked role in shaping the development of cities, particularly in the context of mixed-use and compact urban environments. This paper aims to explore the invisible planning processes inherent in informal practices and their influence on the urban form of Ghanaian cities. By examining the dynamic interplay between informality and formal planning, the study will discuss the ways in which informal actors shape and plan for mixed-use and compact development. Drawing on the synthesis of relevant secondary data, the research will begin by defining urban informality and identifying the factors that contribute to its prevalence in Ghanaian cities. It will delve into the concept of mixed-use and compact development, highlighting its benefits and importance in urban areas. Drawing on case studies, the paper will uncover the hidden planning processes that occur within informal settlements, showcasing their impact on the physical layout, land use, and spatial arrangements of Ghanaian cities. The study will also uncover the challenges and opportunities associated with informal planning. It examines the constraints faced by informal planners (actors) while also exploring the potential benefits and opportunities that emerge when informality is integrated into formal planning frameworks. By understanding the invisible planner, the research will offer valuable insights into how informal practices can contribute to sustainable and inclusive urban development. Based on the findings, the paper will present policy implications and recommendations. It highlights the need to bridge the policy gaps and calls for the recognition of informal planning practices within formal systems. Strategies are proposed to integrate informality into planning frameworks, fostering collaboration between formal and informal actors to achieve compact and mixed-use development in Ghanaian cities. This research underscores the importance of recognizing and leveraging the invisible planner in Ghanaian cities. By embracing informal planning practices, cities can achieve more sustainable, inclusive, and vibrant urban environments that meet the diverse needs of their residents. This research will also contribute to a deeper understanding of the complex dynamics between informality and planning, advocating for inclusive and collaborative approaches that harness the strengths of both formal and informal actors. The findings will likewise contribute to advancing our understanding of informality's role as an invisible yet influential planner, shedding light on its spatial planning implications on Ghanaian cities.

Keywords: informality, mixed-uses, compact development, land use, ghana

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Authors: Zurina Mahadi, Hukil Sino

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United Nations resolved 2030 Sustainable Development Goals (SDGs) in 2015 to complete what Millennium Development Goals did not achieve. Accommodating 17 goals and 169 targets, Sustainable Development Goals are designated to be achieved over the next 15 years. A survey was conducted in July 2019 among the undergraduate students of a public university in Selangor, Malaysia, to learn their selection over Sustainable Development Goals, which they think is the most critical in the Malaysian scenario. This study adopted a qualitative approach, and data is gathered from a single instruction questionnaire administered to a purposive sample of participants. 13 goals were selected by the participants which are Goal 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 16 and 17 while none has selected Goal 7, 9, 14 and 15 which are ‘Affordable and Clean Energy’; ‘Industry, Innovation and Infrastructure’; ‘Life Below Water’ and ‘Life On Land’ respectively. The selected goals are then ranked according to the number of participants who chose that particular goal. Goal 8 is found to be at the highest position of the ranking while Goal 5, 6, 10, and 13 accommodating the lowest position. Goal 8, which is ‘Decent Work and Economic Growth’ is chosen by 13 participants as the most critical goal in Malaysia while Goal 5,6 10, and 13, which are ‘Gender Equality’; ‘Clean Water and Sanitation’; ‘Reduced Inequalities’ and ‘Climate Action’ respectively, are chosen by only one participant each. Issues highlighted by the participants are themed into 10 themes, which are job availability, cost of living, well-being, corruption, education, environment, gender, development planning, consumption, and partnership. The theme of the cost of living has the highest number of issues, followed by the theme of job availability and the environment. The theme of gender has the least number of issues, followed by the theme of corruption and development planning. In principle, these findings, therefore, conclude that from a public university students’ point of view, the most critical sustainable development goal is decent work and economic growth while the most concerning issue is the cost of living. The implications of these findings are students’ knowledge towards the current issues of development, and their views of future sustainable development are considerably high. This study, therefore, suggests their views be inculcated into local, sustainable development frameworks to increase the inclusiveness of the young generation as they are the future SDGs stakeholders.

Keywords: cost of living, inclusiveness, job availability, sustainable development goals

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Authors: Young Min Kim, Jeong Lak Sohn, Eui Soo Yoon

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This study describes the optimization of supercritical carbon dioxide (S-CO2) power cycle for recovering waste heat from a gas turbine. An S-CO2 cycle that recovers heat from small industrial and aeroderivative gas turbines can outperform a steam-bottoming cycle despite its simplicity and compactness. In using S-CO2 power cycles for waste heat recovery, a split cycle was studied to maximize the net output power by incorporating the utilization efficiency of the waste heat (lowering the temperature of the exhaust gas through the heater) along with the thermal efficiency of the cycle (minimizing the temperature difference for the heat transfer, exergy loss). The cooling condition of the S-CO2 WHR system has a great impact on the performance and the optimum low pressure of the system. Furthermore, the optimum high pressure of the S-CO2 WHR systems for the maximum power from the given heat sources is dependent on the temperature of the waste heat source.

Keywords: exergy loss, gas turbine, optimization, supercritical CO2 power cycle, split cycle, waste heat recovery

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Authors: Elnaz Entezar, Reza Ezzati

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In recent decades, trade flows, capital, workforce, technology and information have increased between international borders and the globalization has turned to an undeniable process in international economics. Meanwhile, despite the positive aspects of globalization, the critics of globalization opine that the risks and costs of globalization for developing vulnerable economies and the world's impoverished people are high and significant. In this regard, this study by using the data of KOF Economic Institute and the World Bank for 113 different countries during the period 2002-2012, by taking advantage of panel smooth transition regression, and by taking the gross domestic product as transmission variables discuss the nonlinear relationship between research variables. The results have revealed that globalization in low regime (countries with low GDP) has negative impact whereas in high regime (countries with high GDP) has a positive impact. In spite of the fact that in the early stages of growth, control of corruption has a positive impact on economic growth, after a threshold has a negative impact on economic growth.

Keywords: globalization, corruption, panel smooth transition model, economic growth, threshold, economic convergence

Procedia PDF Downloads 290