Search results for: multi-objective combinatorial optimization problem

Authors: Tien-Ling Yeh, Jo-Han Chan

Abstract:

The percentage of dual-earner couples has become higher and higher each year. Family lifestyles in Taiwan have also been changing. This fact reflects the importance of family communication and parent-child relationship. This study aimed to explore the influences of family lifestyles and accompany forms on children’s capability to solve problems. The research process included two phases: (1) literature review, to explore the characteristics of children’s capability to solve problems and methods to measure this capability; and (2) questionnaire analyses, to explore the influences of lifestyles and accompany time and forms of modern families on their children’s capability to solve problems. The questionnaires were issued in October and November, 2016. A total of 300 questionnaires were retrieved, among which 250 were valid. The findings are summarized below: -The linguistic performances of the children from families of the busy and haggling lifestyle or the intermittent childcare lifestyle were rather good. Besides being interested in learning, these children could solve problems or difficulties independently. -The capability to ‘analyze problems’ of children from families with accompanying time during 19:00-19:30 (family dinner time) or 22:00-23:30 (before bedtime) was good. When facing a complex problem, these children could identify the most important factor in the problem. When seeing a problem, they would first look for the cause. If they encountered a bottleneck while solving a problem, they would review the context of the problem and related conditions to come up with another solution. -According to the literature, learning toys with numbers and symbols to learn to read can help develop children’s logic thinking, which is helpful to solve problems. Interestingly, some study suggested that children playing with fluid constructive toys are less likely to give up what they are doing and more likely to identify problems in their daily life. Some of them can even come up with creative and effective solutions.

Keywords: accompany, lifestyle, parent-child, problem-solving

Procedia PDF Downloads 117

Authors: Amal E. Ahmed, Levent Trabzon

Abstract:

Due to the low concentration of the analytes in biological samples, the use of Biological Microelectromechanical System (Bio-MEMS) biosensors for biomolecules detection results in a minuscule output signal that is not good enough for practical applications. In response to this, a need has arisen for an optimized biosensor capable of giving high output signal in response the detection of few analytes in the sample; the ultimate goal is being able to convert the attachment of a single biomolecule into a measurable quantity. For this purpose, MEMS microcantilevers based biosensors emerged as a promising sensing solution because it is simple, cheap, very sensitive and more importantly does not need analytes optical labeling (Label-free). Among the different microcantilever transducing techniques, piezoresistive based microcantilever biosensors became more prominent because it works well in liquid environments and has an integrated readout system. However, the design of piezoresistive microcantilevers is not a straightforward problem due to coupling between the design parameters, constraints, process conditions, and performance. It was found that the parameters that can be optimized to enhance the sensitivity of Piezoresistive microcantilever-based sensors are: cantilever dimensions, cantilever material, cantilever shape, piezoresistor material, piezoresistor doping level, piezoresistor dimensions, piezoresistor position, Stress Concentration Region's (SCR) shape and position. After a systematic analyzation of the effect of each design and process parameters on the sensitivity, a step-wise optimization approach was developed in which almost all these parameters were variated one at each step while fixing the others to get the maximum possible sensitivity at the end. At each step, the goal was to optimize the parameter in a way that it maximizes and concentrates the stress in the piezoresistor region for the same applied force thus get the higher sensitivity. Using this approach, an optimized sensor that has 73.5x times higher electrical sensitivity (ΔR⁄R) than the starting sensor was obtained. In addition to that, this piezoresistive microcantilever biosensor it is more sensitive than the other similar sensors previously reported in the open literature. The mechanical sensitivity of the final senior is -1.5×10-8 Ω/Ω ⁄pN; which means that for each 1pN (10-10 g) biomolecules attach to this biosensor; the piezoresistor resistivity will decrease by 1.5×10-8 Ω. Throughout this work COMSOL Multiphysics 5.0, a commercial Finite Element Analysis (FEA) tool, has been used to simulate the sensor performance.

Keywords: biosensor, microcantilever, piezoresistive, stress concentration region (SCR)

Procedia PDF Downloads 571

Authors: Omaima N. Ahmad AL-Allaf

Abstract:

Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

Procedia PDF Downloads 226

Authors: Debjani Chakraborty, Abhijit Chatterjee, Aishwaryaprajna

Abstract:

Posynomials, a special type of polynomials, having singularities, pose difficulties while solving geometric programming problems. In this paper, a methodology has been proposed and used to obtain extreme values for geometric programming problems by nth degree polynomial interpolation technique. Here the main idea to optimise the posynomial is to fit a best polynomial which has continuous gradient values throughout the range of the function. The approximating polynomial is smoothened to remove the discontinuities present in the feasible region and the objective function. This spatial interpolation method is capable to optimise univariate and multivariate geometric programming problems. An example is solved to explain the robustness of the methodology by considering a bivariate nonlinear geometric programming problem. This method is also applicable for signomial programming problem.

Keywords: geometric programming problem, multivariate optimisation technique, posynomial, spatial interpolation

Procedia PDF Downloads 371

Authors: Ming Liu, Zhihui Sun, Xiaoning Zhang

Abstract:

This paper studies a deterministic container transportation problem, jointly optimizing the berth allocation, quay crane assignment and yard storage allocation at container ports. The problem is formulated as an integer program to coordinate the decisions. Because of the large scale, it is then transformed into a set partitioning formulation, and a framework of branchand- price algorithm is provided to solve it.

Keywords: branch-and-price, container terminal, joint scheduling, maritime logistics

Procedia PDF Downloads 293

Authors: Han Ik Park, Jeong Hyeon Seong, Dong Seop Han, Su-Chul Shin, Young Chul Park

Abstract:

A Spudcan is mounted on the lower leg of the jack-up rig, a device for preventing a rollover of a structure and to support the structure in a stable sea floor. At the time of inserting the surface of the spud can to penetrate when the sand layer is stable and smoothly pulled to the clay layer, and at that time of recovery when uploading the spud can is equipped with a water injection device. In this study, it is significant to optimize the shape of pipelines holes for water injection device and it was set in two kinds of shape, the oval and round. Interpretation of the subject into the site of Gulf of Mexico offshore Wind Turbine Installation Vessels (WTIV)was chosen as a target platform. Using the ANSYS Workbench commercial programs, optimal design was conducted. The results of this study can be applied to the hole-shaped design of various marine structures.

Keywords: kriging method, jack-up rig, shape optimization, spudcan

Procedia PDF Downloads 508

Authors: A. V. Varfolomeeva, N. S. Tkachenko, A. G. Tishchenko

Abstract:

The problem of violation of internal validity in studies of psychological structures is considered. The role of epistemological attitudes of researchers in the planning of research within the methodology of the system-evolutionary approach is assessed. Alternative programs of psychological research involving representatives of different biological species are presented. On the example of the results of two research series the variants of solving the problem are discussed.

Keywords: epistemological attitudes, experimental design, validity, psychological structure, learning

Procedia PDF Downloads 115

Authors: Pitak Keawbunsong, Sathaporn Promwong

Abstract:

This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

Procedia PDF Downloads 338

Authors: Satish Babu Rajulapati

Abstract:

The removal of toxic and heavy metal contaminants from wastewater streams and industrial effluents is one of the most important environmental issues being faced world over. In the present study three bacterial cultures tolerating high concentrations of chromium were isolated from the soil and wastewater sample collected from the tanneries located in Warangal, Telangana state. The bacterial species were identified as Bacillus sp., Staphylococcus sp. and pseudomonas sp. Preliminary studies were carried out with the three bacterial species at various operating parameters such as pH and temperature. The results indicate that pseudomonas sp. is the efficient one in the uptake of Cr(VI). Further, detailed investigation of Pseudomonas sp. have been carried out to determine the efficiency of removal of Cr(VI). The various parameters influencing the biosorption of Cr(VI) such as pH, temperature, initial chromium concentration, innoculum size and incubation time have been studied. Response Surface Methodology (RSM) was applied to optimize the removal of Cr(VI). Maximum Cr(VI) removal was found to be 85.72% Cr(VI) atpH 7, temperature 35 °C, initial concentration 67mg/l, inoculums size 9 %(v/v) and time 60 hrs.

Keywords: Staphylococcus sp, chromium, RSM, optimization, Cr(IV)

Procedia PDF Downloads 325

Authors: Subrato Saha, Yun-Hyun Cho

Abstract:

In electric power steering (EPS), spoke type brushless ac (BLAC) motors offer distinct advantages over other electric motor types in terms torque smoothness, reliability and efficiency. This paper deals with the shape optimization of spoke type BLAC motor, in order to reduce cogging torque. This paper examines 3 steps skewing rotor angle, optimizing rotor core edge and rotor overlap length for reducing cogging torque in spoke type BLAC motor. The methods were applied to existing machine designs and their performance was calculated using finite- element analysis (FEA). Prototypes of the machine designs were constructed and experimental results obtained. It is shown that the FEA predicted the cogging torque to be nearly reduce using those methods.

Keywords: EPS, 3-Step skewing, spoke type BLAC, cogging torque, FEA, optimization

Procedia PDF Downloads 491

Authors: Harun Aydilek, Asiye Aydilek, Ali Allahverdi

Abstract:

Our objective is to minimize the total tardiness in an m-machine two-stage assembly flowshop scheduling problem. The objective is an important performance measure because of the fact that the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. In the literature, the problem is considered with zero setup times which may not be realistic and appropriate for some scheduling environments. Considering separate setup times from processing times increases machine utilization by decreasing the idle time and reduces total tardiness. We propose two new algorithms and adapt four existing algorithms in the literature which are different versions of simulated annealing and genetic algorithms. Moreover, a dominance relation is developed based on the mathematical formulation of the problem. The developed dominance relation is incorporated in our proposed algorithms. Computational experiments are conducted to investigate the performance of the newly proposed algorithms. We find that one of the proposed algorithms performs significantly better than the others, i.e., the error of the best algorithm is less than those of the other algorithms by minimum 50%. The newly proposed algorithm is also efficient for the case of zero setup times and performs better than the best existing algorithm in the literature.

Keywords: algorithm, assembly flowshop, scheduling, simulation, total tardiness

Procedia PDF Downloads 329

Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

Procedia PDF Downloads 563

Authors: Noradin Ghadimi, Nima Amjady, Oveis Abedinia, Roza Poursoleiman

Abstract:

This paper proposed an Improved Honey Bee Mating Optimization (IHBMO) for a planning paradigm for network upgrade. The proposed technique is a new meta-heuristic algorithm which inspired by mating of the honey bee. The paradigm is able to select amongst several choices equi-cost one assuring the optimum in terms of voltage profile, considering various scenarios of DG penetration and load demand. The distributed generation (DG) has created a challenge and an opportunity for developing various novel technologies in power generation. DG prepares a multitude of services to utilities and consumers, containing standby generation, peaks chopping sufficiency, base load generation. The proposed algorithm is applied over the 30 lines, 28 buses power system. The achieved results demonstrate the good efficiency of the DG using the proposed technique in different scenarios.

Keywords: distributed generation, IHBMO, renewable energy units, network upgrade

Procedia PDF Downloads 487

Authors: Shahin Mirshekari, Mohammadreza Moradi, Hossein Jafari, Mehdi Jafari, Mohammad Ensaf

Abstract:

This research employs Gaussian Process Regression (GPR) with an ensemble kernel, integrating Exponential Squared, Revised Matern, and Rational Quadratic kernels to analyze pharmaceutical sales data. Bayesian optimization was used to identify optimal kernel weights: 0.76 for Exponential Squared, 0.21 for Revised Matern, and 0.13 for Rational Quadratic. The ensemble kernel demonstrated superior performance in predictive accuracy, achieving an R² score near 1.0, and significantly lower values in MSE, MAE, and RMSE. These findings highlight the efficacy of ensemble kernels in GPR for predictive analytics in complex pharmaceutical sales datasets.

Keywords: Gaussian process regression, ensemble kernels, bayesian optimization, pharmaceutical sales analysis, time series forecasting, data analysis

Procedia PDF Downloads 71

Authors: Babu Veeregowda, Rongfang Liu

Abstract:

The current traffic impact assessment methodology and environmental quality review process for approval of land development project are conventional, stagnant, and one-dimensional. The environmental review policy and procedure lacks in providing the direction to regulate or seek alternative land uses and sizes that exploits the existing or surrounding elements of built environment (‘4 D’s’ of development – Density, Diversity, Design, and Distance to Transit) or smart growth principles which influence the travel behavior and have a significant effect in reducing vehicular traffic. Additionally, environmental review policy does not give directions on how to incorporate urban planning into the development in ways such as incorporating non-motorized roadway elements such as sidewalks, bus shelters, and access to community facilities. This research developed a methodology to optimize the mix of land uses and sizes using the heuristic optimization process to minimize the auto dependency development and to meet the interests of key stakeholders. A case study of Willets Point Mixed Use Development in Queens, New York, was used to assess the benefits of the methodology. The approved Willets Point Mixed Use project was based on maximum envelop of size and land use type allowed by current conventional urban renewal plans. This paper will also evaluate the parking accumulation for various land uses to explore the potential for shared parking to further optimize the mix of land uses and sizes. This research is very timely and useful to many stakeholders interested in understanding the benefits of integrated land uses and its development.

Keywords: traffic impact, mixed use, optimization, trip generation

Procedia PDF Downloads 214

Authors: Kanya L. Khatri, Ashfaque A. Memon, Rod J. Smith, Shamas Bilal

Abstract:

The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurized systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30 to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption and cause significant greenhouse gas emissions. Hence, a balance between the improvement in water use and the potential increase in energy consumption is required keeping in view adverse impact of increased carbon emissions on the environment. When surface water is used, pressurized systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation. With gravity based surface irrigation methods the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimization and control of surface irrigation and surface irrigation with real-time optimization has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is almost equivalent to that given by pressurized systems. Thus real-time optimization and control offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.

Keywords: pressurised irrigation, carbon emissions, real-time, environmentally-friendly, REIP

Procedia PDF Downloads 503

Authors: César Garza

Abstract:

In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

Procedia PDF Downloads 130

Authors: Karen Odendaal

Abstract:

Accounting transactions are becoming more complex, and more extensive accounting guidance is provided on a continuous basis. It is widely perceived that conceptual teaching of accounting contributes to lifelong learning. Such a conceptual teaching approach also contributes to effective accounting problem-solving. This framework-based approach is rooted in educational psychologies such as constructivism and Ausubel’s subsumption theory. This study aimed at investigating the ability of students to solve complex accounting problems by using only concepts underlying the Conceptual Framework. An assignment was administered to pre-graduate students at a South African university and this study made use of an interpretative research design which implemented multiple research instruments to investigate the ability of students to solve complex accounting problems using only concepts underlying the Conceptual Framework. Student perceptions were analysed and were aided by a related reflective questionnaire. The importance of the study indicates the necessity of Accounting educators to enhance a conceptual understanding among students as a mechanism for problem-solving of accounting issues. The results indicate that the ability of students to solve accounting problems effectively using only the Conceptual Framework depends on the complexity of the scenario and the students’ familiarity with the problem. The study promotes a balanced and more conceptual (rather than only technical) preference to the problem-solving of complex accounting problems. The study indubitably promotes considerable emphasis on the importance of the Conceptual Framework in accounting education and the promotion of life-long learning in the subject field.

Keywords: accounting education, conceptual teaching, constructivism, framework-based, problem-solving

Procedia PDF Downloads 233

Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

Abstract:

Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

Procedia PDF Downloads 399

Authors: Sanchai Ratthanakwan

Abstract:

This research aims to study situations and characteristics of the problems facing the urban poor. The data and information are collected by focus group and in-depth interview leader and members of Four Regions Slum Network, community representatives and the social welfare officer. The research can be concluded that the problems of the urban poor faced with three major problems: Firstly, the shortage of housing and stability issues in housing; secondly, the problem of substandard quality of life; and thirdly, the debt problem. The study found that a solution will be found in two ways: First way is the creation of housing for the urban poor in slums or community intrusion by the state. Second way is the stability in the housing and subsistence provided by the community center called “housing stability”.

Keywords: urban poor, social welfare, Bangkok metropolis, housing stability

Procedia PDF Downloads 424

Authors: Wajahat Ali, Shakeel Javaid

Abstract:

In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

Procedia PDF Downloads 83

Authors: H. Nikzad, S. Yoshitomi

Abstract:

This paper presents the design application and reinforcement detailing of 15 storied reinforced concrete shear wall-frame structure based on linear static analysis. Databases are generated for section sizes based on automated structural optimization method utilizing Active-set Algorithm in MATLAB platform. The design constraints of allowable section sizes, capacity criteria and seismic provisions for static loads, combination of gravity and lateral loads are checked and determined based on ASCE 7-10 documents and ACI 318-14 design provision. The result of this study illustrates the efficiency of proposed method, and is expected to provide a useful reference in designing of RC shear wall-frame structures.

Keywords: design constraints, ETABS, linear static analysis, MATLAB, RC shear wall-frame structures, structural optimization

Procedia PDF Downloads 261

Authors: Saqib Ali

Abstract:

Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

Procedia PDF Downloads 97

Authors: F. Gökgöz, M. E. Atmaca

Abstract:

Electricity has an indispensable role in human daily life, technological development and economy. It is a special product or service that should be instantaneously generated and consumed. Sources of the world are limited so that effective and efficient use of them is very important not only for human life and environment but also for technological and economic development. Competitive electricity market is one of the important way that provides suitable platform for effective and efficient use of electricity. Besides benefits, it brings along some risks that should be carefully managed by a market player like Electricity Generation Company. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Value at Risk methods for case studies. Performance of optimal electricity sale solutions are measured and the portfolio performance has been evaluated via Sharpe-Ratio, and compared with conventional approach. Biennial historical electricity price data of Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: electricity market, portfolio optimization, risk management, value at risk

Procedia PDF Downloads 313

Authors: Florian Gschösser, Walter Purrer

Abstract:

The paper shows examples for the (environmental) optimization of production processes for asphalt mixtures applied for typical road pavements in Austria and Switzerland. The conducted “from-cradle-to-gate” LCA firstly analyzes the production one cubic meter of asphalt and secondly all material production processes for exemplary highway pavements applied in Austria and Switzerland. It is shown that environmental impacts can be reduced by the application of reclaimed asphalt pavement (RAP) and by the optimization of specific production characteristics, e.g. the reduction of the initial moisture of the mineral aggregate and the reduction of the mixing temperature by the application of low-viscosity and foam bitumen. The results of the LCA study demonstrate reduction potentials per cubic meter asphalt of up to 57 % (Global Warming Potential–GWP) and 77 % (Ozone depletion–ODP). The analysis per square meter of asphalt pavement determined environmental potentials of up to 40 % (GWP) and 56 % (ODP).

Keywords: asphalt mixtures, environmental potentials, life cycle assessment, material production

Procedia PDF Downloads 532

Authors: Serhat Tüzün, Tufan Demirel

Abstract:

The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

Procedia PDF Downloads 412

Authors: Mia Françoise

Abstract:

This report aims to develop a strategy for assisting short-term investors to benefit from the current economic climate in South Africa by utilizing technical analysis techniques and predictive analytics. As part of this research, value investing and technical analysis principles will be combined to maximize returns for South African investors while optimizing volatility. As an emerging market, South Africa offers many opportunities for high growth in sectors where other developed countries cannot grow at the same rate. Investing in South African companies with significant growth potential can be extremely rewarding. Although the risk involved is more significant in countries with less developed markets and infrastructure, there is more room for growth in these countries. According to recent research, the offshore market is expected to outperform the local market over the long term; however, short-term investments in the local market will likely be more profitable, as the Johannesburg Stock Exchange is predicted to outperform the S&P500 over the short term. The instabilities in the economy contribute to increased market volatility, which can benefit investors if appropriately utilized. Price prediction and portfolio optimization comprise the two primary components of this methodology. As part of this process, statistics and other predictive modeling techniques will be used to predict the future performance of stocks listed on the Johannesburg Stock Exchange. Following predictive data analysis, Modern Portfolio Theory, based on Markowitz's Mean-Variance Theorem, will be applied to optimize the allocation of assets within an investment portfolio. By combining different assets within an investment portfolio, this optimization method produces a portfolio with an optimal ratio of expected risk to expected return. This methodology aims to provide a short-term investment with a stock portfolio that offers the best risk-to-return profile for stocks listed on the JSE by combining price prediction and portfolio optimization.

Keywords: financial stocks, optimized asset allocation, prediction modelling, South Africa

Procedia PDF Downloads 98

Authors: Christoph Opperer

Abstract:

The rapid urbanization of modern societies and the need for sustainable urban development demand innovative solutions that meet both individual and collective needs while addressing environmental concerns. To address these challenges, this paper presents a study that explores the potential of spatial and energetic/ecological optimization to enhance the performance of urban settlements, focusing on both architectural and urban scales. The study focuses on the application of biological principles and self-organization processes in urban planning and design, aiming to achieve a balance between ecological performance, architectural quality, and individual living conditions. The research adopts a case study approach, focusing on a 10-hectare brownfield site in the south of Vienna. The site is surrounded by a small-scale built environment as an appropriate starting point for the research and design process. However, the selected urban form is not a prerequisite for the proposed design methodology, as the findings can be applied to various urban forms and densities. The methodology used in this research involves dividing the overall building mass and program into individual small housing units. A computational model has been developed to optimize the distribution of these units, considering factors such as solar exposure/radiation, views, privacy, proximity to sources of disturbance (such as noise), and minimal internal circulation areas. The model also ensures that existing vegetation and buildings on the site are preserved and incorporated into the optimization and design process. The model allows for simultaneous optimization at two scales, architectural and urban design, which have traditionally been addressed sequentially. This holistic design approach leads to individual and collective benefits, resulting in urban environments that foster a balance between ecology and architectural quality. The results of the optimization process demonstrate a seemingly random distribution of housing units that, in fact, is a densified hybrid between traditional garden settlements and allotment settlements. This urban typology is selected due to its compatibility with the surrounding urban context, although the presented methodology can be extended to other forms of urban development and density levels. The benefits of this approach are threefold. First, it allows for the determination of ideal housing distribution that optimizes solar radiation for each building density level, essentially extending the concept of sustainable building to the urban scale. Second, the method enhances living quality by considering the orientation and positioning of individual functions within each housing unit, achieving optimal views and privacy. Third, the algorithm's flexibility and robustness facilitate the efficient implementation of urban development with various stakeholders, architects, and construction companies without compromising its performance. The core of the research is the application of global and local optimization strategies to create efficient design solutions. By considering both, the performance of individual units and the collective performance of the urban aggregation, we ensure an optimal balance between private and communal benefits. By promoting a holistic understanding of urban ecology and integrating advanced optimization strategies, our methodology offers a sustainable and efficient solution to the challenges of modern urbanization.

Keywords: sustainable development, self-organization, ecological performance, solar radiation and exposure, daylight, visibility, accessibility, spatial distribution, local and global optimization

Procedia PDF Downloads 66

Authors: Kevin Worrall, Euan McGookin

Abstract:

The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

Procedia PDF Downloads 239

Authors: Blair D. Macdonald

Abstract:

After nearly one hundred years of its origin, foundational quantum mechanics remains one of the greatest unexplained mysteries in physicists today. Within this time, chaos theory and its geometry, the fractal, has developed. In this paper, the propagation behaviour with an iteration of a simple fractal, the Koch Snowflake, was described and analysed. From an arbitrary observation point within the fractal set, the fractal propagates forward by oscillation—the focus of this study and retrospectively behind by exponential growth from a point beginning. It propagates a potentially infinite exponential oscillating sinusoidal wave of discrete triangle bits sharing many characteristics of light and quantum entities. The model's wave speed is potentially constant, offering insights into the perception and a direction of time where, to an observer, when travelling at the frontier of propagation, time may slow to a stop. In isolation, the fractal is a superposition of component bits where position and scale present a problem of location. In reality, this problem is experienced within fractal landscapes or fields where 'position' is only 'known' by the addition of information or markers. The quantum' measurement problem', 'uncertainty principle,' 'entanglement,' and the classical-quantum interface are addressed; these are a problem of scale invariance associated with isolated fractality. Dual forward and retrospective perspectives of the fractal model offer the opportunity for unification between quantum mechanics and cosmological mathematics, observations, and conjectures. Quantum and cosmological problems may be different aspects of the one fractal geometry.

Keywords: measurement problem, observer, entanglement, unification

Procedia PDF Downloads 90