Search results for: performance optimization

Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modelling have constantly been a challenge through history for human being. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: auto-calibration, Gilan, large-scale water resources, simulation

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Authors: Mohammad Reza Boromand, Masoud Moradi, Amin Eskandari

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The present study attempts to determine ranking of managerial parameters impacting upon performance of football referees in Iran. The population consisted of all referees in Leagues 1, 2 and 3 as well as super league of Iran (N=273), of which we selected 160 referees and assistant referees in 2013-2014. A research-designed questionnaire was used for data collection which was divided into two sections: (1) Demographic details (age range, Marital status, employment, refereeing experience, education level, refereeing level and proficiency) and (2) items related to parameters impacting upon performance of referees (structural parameters, operational parameters, environmental parameters, temporal parameters, economic parameters, facilities and tools, personal performance and performance evaluation). Internal consistency was calculated by Cronbach's alpha (r=0.85). For data analysis, we performed Freedman's Test and used SPSS software (α>0.05), along with descriptive statistics. The findings showed the following ranking for the above-mentioned managerial parameters: Facilities and tools, personal performance, economic parameters, structural parameters, operational parameters, environmental parameters, temporal parameters, and performance evaluation.

Keywords: Iran, football referees, managerial parameters, performance

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Authors: Sanjay Kumar Parjapati, Ajai Jain

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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

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Authors: Anne Kariuki, Kellen Kiambati

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The broad objective of this study was to establish the mediating effect of media visibility on the relationship between corporate Social Responsibility (CSR) and the corporate performance of firms listed on the Nairobi Securities Exchange. The review of the literature provided conceptual and empirical gaps that formed the basis of the conceptual hypotheses. A survey questionnaire was distributed to the 50 heads of human resource departments in the different firms. A survey was conducted on fifty (50) companies listed on the Nairobi Securities Exchange. The study findings reported a significant relationship between CSR and non-financial performance and the mediating role of media visibility on the relationship between CSR and performance. The findings of the study support the signaling theory and stakeholder’s theory. Conclusively, CSR activities have an effect on media visibility, which in turn affects performance.

Keywords: corporate social responsibility, media visibility, corporate performance, non-financial performance

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

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Authors: M. M. Nor, H. I. Sheikh, M. F. H. Hassan, S. Mokhtar, A. Suganthi, A. Fadhlina

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Black grass jelly (BGJ) is a popular black jelly used in preparing various drinks and desserts. Food industries often use preservatives to maintain the physicochemical properties of foods, such as color and texture. These preservatives (e.g., phosphoric acid) are linked with deleterious health effects such as kidney disease. Using gelling agents, carrageenan, and gelatin to make BGJ could improve its physiochemical and textural properties. This study was designed to optimize BGJ-selected physicochemical and textural properties using carrageenan and gelatin. Various black grass jelly formulations (BGJF) were designed using an I-optimal mixture design in Design Expert® software. Data from commercial BGJ were used as a reference during the optimization process. The combination of carrageenan and gelatin added to the formulations was up to 14.38g (~5%), respectively. The results showed that adding 2.5g carrageenan and 2.5g gelatin at approximately 5g (~5%) effectively maintained most of the physiochemical properties with an overall desirability function of 0.81. This formulation was selected as the optimum black grass jelly formulation (OBGJF). The leaching properties and floating duration were measured on the OBGJF and commercial grass jelly for 20 min and 40 min, respectively. The results indicated that OBGJF showed significantly (p<0.0001) lower leaching rate and floating time (p<0.05). Hence, further optimization is needed to increase the floating duration of carrageenan and gelatin-based BGJ.

Keywords: cincau, Mesona chinensis, black grass jelly, carrageenan, gelatin

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Authors: Pin-Ling Yin, Dung-Ying Lin

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Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: Mohammad Mahdi Mousavi

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Bankruptcy prediction models have been implemented for continuous evaluation and monitoring of firms. With the huge number of bankruptcy models, an extensive number of studies have focused on answering the question that which of these models are superior in performance. In practice, one of the drawbacks of existing comparative studies is that the relative assessment of alternative bankruptcy models remains an exercise that is mono-criterion in nature. Further, a very restricted number of criteria and measure have been applied to compare the performance of competing bankruptcy prediction models. In this research, we overcome these methodological gaps through implementing an extensive range of criteria and measures for comparison between dynamic and static bankruptcy models, and through proposing a multi-criteria framework to compare the relative performance of bankruptcy models in forecasting firm distress for UK firms.

Keywords: bankruptcy prediction, data envelopment analysis, performance criteria, performance measures

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Authors: Ivan Ramos Sampe Immanuel, Linung Kresno Adikusumo, Liston Sitanggang

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Achieving the production targets of oil and gas in an upstream oil and gas company represents a complex undertaking necessitating collaborative engagement from a multidisciplinary team. In addition to conducting exploration activities and executing well intervention programs, an upstream oil and gas enterprise must assess the feasibility of attaining predetermined production goals. The monitoring of production performance serves as a critical activity to ensure organizational progress towards the established oil and gas performance targets. Subsequently, decisions within the upstream oil and gas management team are informed by the received information pertaining to the respective production performance. To augment the decision-making process, the implementation of a production performance dashboard emerges as a viable solution, providing an integrated and centralized tool. The deployment of a production performance dashboard manifests as an instrumental mechanism fostering a user-friendly interface for monitoring production performance, while concurrently preserving the intrinsic characteristics of granular data. The integration of diverse data sources into a unified production performance dashboard establishes a singular veritable source, thereby enhancing the organization's capacity to uphold a consolidated and authoritative foundation for its business requisites. Additionally, the heightened accessibility of the production performance dashboard to business users constitutes a compelling substantiation of its consequential impact on facilitating the monitoring of organizational targets.

Keywords: production, performance, dashboard, data analytics

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: Ajith J. Kings, L. R. Monisha Miriam, R. Edwin Raj, S. Julyes Jaisingh, S. Gavaskar

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Microalgae are a potential bio-source for rejuvenated solutions in various disciplines of science and technology, especially in medicine and energy. Biodiesel is being replaced for conventional fuels in automobile industries with reduced pollution and equivalent performance. Since it is a carbon neutral fuel by recycling CO2 in photosynthesis, global warming potential can be held in control using this fuel source. One of the ways to meet the rising demand of automotive fuel is to adopt with eco-friendly, green alternative fuels called sustainable microalgal biodiesel. In this work, a microalga Chlamydomonas reinhardtii was cultivated and optimized in different media compositions developed from under-utilized waste materials in lab scale. Using the optimized process conditions, they are then mass propagated in out-door ponds, harvested, dried and oils extracted for optimization in ambient conditions. The microalgal oil was subjected to two step esterification processes using acid catalyst to reduce the acid value (0.52 mg kOH/g) in the initial stage, followed by transesterification to maximize the biodiesel yield. The optimized esterification process parameters are methanol/oil ratio 0.32 (v/v), sulphuric acid 10 vol.%, duration 45 min at 65 ºC. In the transesterification process, commercially available alkali catalyst (KOH) is used and optimized to obtain a maximum biodiesel yield of 95.4%. The optimized parameters are methanol/oil ratio 0.33(v/v), alkali catalyst 0.1 wt.%, duration 90 min at 65 ºC 90 with smooth stirring. Response Surface Methodology (RSM) is employed as a tool for optimizing the process parameters. The biodiesel was then characterized with standard procedures and especially by GC-MS to confirm its compatibility for usage in internal combustion engine.

Keywords: microalgae, organic media, optimization, transesterification, characterization

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Authors: B. Marasović, S. Pivac, S. V. Vukasović

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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

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Authors: Xhaklina Cani, Ilirjan Malollari, Ismet Beqiraj, Lorina Lici

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Oil characterization is an essential step in the design, simulation, and optimization of refining facilities. To achieve optimal crude selection and processing decisions, a refiner must have exact information refer to crude oil quality. This includes crude oil TBP-curve as the main data for correct operation of refinery crude oil atmospheric distillation plants. Crude oil is typically characterized based on a distillation assay. This procedure is reasonably well-defined and is based on the representation of the mixture of actual components that boil within a boiling point interval by hypothetical components that boil at the average boiling temperature of the interval. The crude oil assay typically includes TBP distillation according to ASTM D-2892, which can characterize this part of oil that boils up to 400 C atmospheric equivalent boiling point. To model the yield curves obtained by physical distillation is necessary to compare the differences between the modelling and the experimental data. Most commercial use a different number of components and pseudo-components to represent crude oil. Laboratory tests include distillations, vapor pressures, flash points, pour points, cetane numbers, octane numbers, densities, and viscosities. The aim of the study is the drawing of true boiling curves for different crude oil resources in Albania and to compare the differences between the modeling and the experimental data for optimal characterization of crude oil.

Keywords: TBP distillation curves, crude oil, optimization, simulation

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

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Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: offshore fields of hydrocarbons of the Baltic Sea, development of offshore oil and gas fields, optimization of the field development scheme, solution of multicriteria tasks in oil and gas complex, quality management in oil and gas complex

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Authors: Ali Abdullah Albezaghi

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This article aims to introduce a conceptual framework that can facilitate investigations concerning the role of risk management practices in the relationship between construction risks and the construction project's performance. This article is structured based on the extant literature; it reviews theoretical perspectives, highlights the gaps, and illustrates the significance of developing a framework of suggested relationships. Despite growing interest in the role of risks in construction project performance, previous studies have paid little attention to investigating the moderating role of risk management practices on the risk-performance link. This has left researchers and construction project managers with minimal information to explain the conditions under which risk management practices can reduce the impact of project-related risks and improve performance. In this context, this article suggests a viable research model with propositions that assess risk-performance relationships and discusses the potential moderating effects on the domain relationship. This paper adds to the risk management literature by focusing on risk variables that directly impact performance. Further, it also considers the moderating role of risk management practices in such relationships.

Keywords: risk management practices, external risks, internal risks, project risks, project performance

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Authors: Francesca Schiavello

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This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

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Authors: Djeffal Asma, Zemmouri Noureddine

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In order for building designer to be able to balance environmental concerns with other performance requirements, they need clear and concise information. For certain decisions during the design process, qualitative guidance, such as design checklists or guidelines information may not be sufficient for evaluating the environmental benefits between different building materials, products and designs. In this case, quantitative information, such as that generated through a life cycle assessment, provides the most value. LCA provides a systematic approach to evaluating the environmental impacts of a product or system over its entire life. In the case of buildings life cycle includes the extraction of raw materials, manufacturing, transporting and installing building components or products, operating and maintaining the building. By integrating LCA into building design process, designers can evaluate the life cycle impacts of building design, materials, components and systems and choose the combinations that reduce the building life cycle environmental impact. This article attempts to give an overview of the integration of LCA methodology in the context of building design, and focuses on the use of this methodology for environmental considerations concerning process design and optimization. A multiple case study was conducted in order to assess the benefits of the LCA as a decision making aid tool during the first stages of the building design under specific climate conditions of the North East region of Algeria. It is clear that the LCA methodology can help to assess and reduce the impact of a building design and components on the environment even if the process implementation is rather long and complicated and lacks of global approach including human factors. It is also demonstrated that using LCA as a multi objective optimization of building process will certainly facilitates the improvement in design and decision making for both new design and retrofit projects.

Keywords: life cycle assessment, buildings, sustainability, elementary schools, environmental impacts

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion

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Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.

Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law

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Authors: Dina Tamazin, Nicoleta Tipi, Sahar Validi

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The oil refining industry plays vital role in the world economy. Oil refining companies operate in a more complex and dynamic environment than ever before. In addition, oil refining companies and the public are becoming more conscious of crude oil scarcity and climate changes. Hence, sustainability in the oil refining industry is becoming increasingly critical to the industry's long-term viability and to the environmental sustainability. Mainly, it is relevant to the measurement and evaluation of the company's sustainable performance to support the company in understanding their performance and its implication more objectively and establishing sustainability development plans. Consequently, the oil refining companies attempt to re-engineer their supply chain to meet the sustainable goals and standards. On the other hand, this research realized that previous research in oil refining sustainable supply chain performance measurements reveals that there is a lack of studies that consider the integration of sustainability in the supply chain performance measurement practices in the oil refining industry. Therefore, there is a need for research that provides performance guidance, which can be used to measure sustainability and assist in setting sustainable goals for oil refining supply chains. Accordingly, this paper aims to present a comprehensive oil refining sustainable supply chain performance measurement theoretical framework. In development of this theoretical framework, the main characteristics of oil refining industry have been identified. For this purpose, a thorough review of relevant literature on performance measurement models and sustainable supply chain performance measurement models has been conducted. The comprehensive oil refining sustainable supply chain performance measurement theoretical framework introduced in this paper aims to assist oil refining companies in measuring and evaluating their performance from a sustainability aspect to achieve sustainable operational excellence.

Keywords: oil refining industry, oil refining sustainable supply chain, performance measurement, sustainability

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Authors: Abolfazl Ghelichi, Ghasem Modarresi

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The problem with interpretation courses arises from the fact that Interpretation Courses at University levels are presented by most of the instructors based on listening activities and testing listening performance while interpretation strategies have been underrated. The data are gathered from30 students majoring in Translation Studies to fulfill the major aims of the study including. The study aimed at: 1) examining the significant relationship between specific interpretation strategies and interpretation performance of translation students in interpretation courses, 2) investigating the significant difference between males and females in their interpretation performance, and 3) exploring the interpretation strategies which are more effective for the translation students to improve their interpretation performance from students’ opinions. The results of the study revealed that there was a statistically significant difference in the mean scores for the two groups. The experimental group outperformed the control group in their interpretation performance and the effect size was large. However, there was no significant difference between male and female with respect to their cognition [t (28) =.79, p<.05]. As for the results obtained from the interviews with the students, the commonalities emerged from the students’ responses were analyzed and reported by the researchers.

Keywords: anticipation, interpretation performance, interpretation strategy, shadowing

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Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

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Authors: C. V. Chen, Y. H. Jeng, S. J. Wang

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Leadership is essential to enhancing followers’ psychological empowerment and has an effect on their willingness to take on extra-role behavior and aim for greater performance. Authentic leadership is confirmed to promote employees’ positive affect, psychological empowerment, well-being, and performance. Employees’ spontaneous undertaking of organizationally desired behaviors allows organizations’ gaining the edge in the fiercely competitive business environment. Apart from the contextual factor of leadership, individuals’ goal orientation is found to be highly related to his/her performance. To better understand the psychological process and potential moderation of personal goal orientation, this study investigates the effect of authentic leadership on employees’ task performance and organizational citizenship behavior by including psychological empowerment as the mediating factor and goal orientation as the moderating factor.

Keywords: authentic leadership, task performance, organizational citizenship behavior, goal orientation

Procedia PDF Downloads 790

Authors: Ahmed Aljudaya, Derek Ingham, Lin Ma, Kevin Hughes, Mohammed Pourkashanian

Abstract:

Researchers, power companies, and state politicians have given concentrated solar power (CSP) much attention due to its capacity to generate large amounts of electricity whereas overcoming the intermittent nature of solar resources. The Linear Fresnel Reflector (LFR) is a well-known CSP technology type for being inexpensive, having a low land use factor, and suffering from low optical efficiency. The LFR was considered a cost-effective alternative option to the Parabolic Trough Collector (PTC) because of its simplistic design, and this often outweighs its lower efficiency. The LFR has been found to be a promising option for directly producing steam to a thermal cycle in order to generate low-cost electricity, but also it has been shown to be promising for indirect steam generation. The purpose of this important analysis is to compare the annual performance of the Direct Steam Generation (DSG) and Indirect Steam Generation (ISG) of LFR power plants using molten salt and other different Heat Transfer Fluids (HTF) to investigate their technical and economic effects. A 50 MWe solar-only system is examined as a case study for both steam production methods in extreme weather conditions. In addition, a parametric analysis is carried out to determine the optimal solar field size that provides the lowest Levelized Cost of Electricity (LCOE) while achieving the highest technical performance. As a result of optimizing the optimum solar field size, the solar multiple (SM) is found to be between 1.2 – 1.5 in order to achieve as low as 9 Cent/KWh for the direct steam generation of the linear Fresnel reflector. In addition, the power plant is capable of producing around 141 GWh annually and up to 36% of the capacity factor, whereas the ISG produces less energy at a higher cost. The optimization results show that the DSG’s performance overcomes the ISG in producing around 3% more annual energy, 2% lower LCOE, and 28% less capital cost.

Keywords: concentrated solar power, levelized cost of electricity, linear Fresnel reflectors, steam generation

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Authors: Hanwei Gao, Louis Jezequel, Eric Cabrol, Bernard Vitry

Abstract:

The chassis system is composed of complex elements that take up all the loads from the tire-ground contact area and thus it plays an important role in numerous specifications such as durability, comfort, crash, etc. During the development of new vehicle projects in Renault, durability validation is always the main focus while deployment of comfort comes later in the project. Therefore, sometimes design choices have to be reconsidered because of the natural incompatibility between these two specifications. Besides, robustness is also an important point of concern as it is related to manufacturing costs as well as the performance after the ageing of components like shock absorbers. In this paper an approach is proposed aiming to realize a multi-objective optimization between chassis endurance and comfort while taking the random factors into consideration. The adaptive-sparse polynomial chaos expansion method (PCE) with Chebyshev polynomial series has been applied to predict responses’ uncertainty intervals of a system according to its uncertain-but-bounded parameters. The approach can be divided into three steps. First an initial design of experiments is realized to build the response surfaces which represent statistically a black-box system. Secondly within several iterations an optimum set is proposed and validated which will form a Pareto front. At the same time the robustness of each response, served as additional objectives, is calculated from the pre-defined parameter intervals and the response surfaces obtained in the first step. Finally an inverse strategy is carried out to determine the parameters’ tolerance combination with a maximally acceptable degradation of the responses in terms of manufacturing costs. A quarter car model has been tested as an example by applying the road excitations from the actual road measurements for both endurance and comfort calculations. One indicator based on the Basquin’s law is defined to compare the global chassis durability of different parameter settings. Another indicator related to comfort is obtained from the vertical acceleration of the sprung mass. An optimum set with best robustness has been finally obtained and the reference tests prove a good robustness prediction of Chebyshev PCE method. This example demonstrates the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

Keywords: chassis durability, Chebyshev polynomials, multi-objective optimization, polynomial chaos expansion, ride comfort, robust design

Procedia PDF Downloads 151

Authors: Amizawati Mohd Amir, Ruhanita Maelah, Zaidi Mohd Noor

Abstract:

As part of the Malaysia Higher Institutions' Strategic Plan in promoting high-quality research and education, the Ministry of Higher Education has introduced various instrument to assess the universities performance. The aims are that university will produce more commercially-oriented research and continue to contribute in producing professional workforce for domestic and foreign needs. Yet the spirit of the success lies in the commitment of university particularly the academic staff to translate the vision into reality. For that reason, the element of fairness and justice in assessing individual academic staff performance is crucial to promote directly linked between university and individual work goals. Focusing on public research universities (RUs) in Malaysia, this study observes at the issue through the practice of university contemporary performance measurement system. Accordingly management control theory has conceptualized that contemporary performance measurement consisting of three dimension namely strategic, comprehensive and dynamic building upon equity theory, the relationships between contemporary performance measurement system and organizational justice and in turn the effect on academic staff work performance are tested based on online survey data administered on 365 academic staff from public RUs, which were analyzed using statistics analysis SPSS and Equation Structure Modeling. The findings validated the presence of strategic, comprehensive and dynamic in the contemporary performance measurement system. The empirical evidence also indicated that contemporary performance measure and procedural justice are significantly associated with work performance but not for distributive justice. Furthermore, procedural justice does mediate the relationship between contemporary performance measurement and academic staff work performance. Evidently, this study provides evidence on the importance of perceptions of justice towards influencing academic staff work performance. This finding may be a fruitful input in the setting up academic staff performance assessment policy.

Keywords: comprehensive, dynamic, distributive justice, contemporary performance measurement system, strategic, procedure justice, work performance

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Authors: Daniyar Seitenov, Nazim Mir-Nasiri

Abstract:

Optimization of horizontal axis semi-exposed wind turbine has been performed using a shield protection that automatically protects the generator shaft at extreme wind speeds from over speeding, mechanical damage and continues generating electricity during the high wind speed conditions. A semi-exposed to wind generator has been designed and its structure has been described in this paper. The simplified point-force dynamic load model on the blades has been derived for normal and extreme wind conditions with and without shield involvement. Numerical simulation has been conducted at different values of wind speed to study the efficiency of shield application. The obtained results show that the maximum power generated by the wind turbine with shield does not exceed approximately the rated value of the generator, where shield serves as an automatic break for extreme wind speed values of 15 m/sec and above. Meantime the wind turbine without shield produced a power that is much larger than the rated value. The optimized horizontal axis semi-exposed wind turbine with shield protection is suitable for low and medium power generation when installed on the roofs of high rise buildings for harvesting wind energy. Wind shield works automatically with no power consumption. The structure of the generator with the protection, math simulation of kinematics and dynamics of power generation has been described in details in this paper.

Keywords: renewable energy, wind turbine, wind turbine optimization, high wind speed

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Authors: Ahmad Fahad Alotaibi, Khalid Hamed Hajri, Humoud Hudiban Rashidi

Abstract:

Intelligent information technology infrastructure is considered one of the enablers to enhance digital transformation in the gas and oil fields to optimize IT infrastructure reliability by supporting operations and maintenance in a safe and secure method to optimize resources. Smart IT buildings, communication rooms and shelters with intelligent technologies can strengthen the performance and profitability of gas and oil companies by ensuring business continuity. This paper describes the advantages of deploying intelligent IT infrastructure in the oil and gas industry by illustrating its positive impacts on some development aspects, for instance, operations, maintenance, safety, security and resource optimization. Moreover, it highlights the challenges and difficulties of providing smart IT services in a remote area and proposes solutions to overcome such difficulties.

Keywords: intelligent IT infrastructure, remote areas, oil and gas field, digitalization

Procedia PDF Downloads 58