Search results for: analysis of optimization

Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

Procedia PDF Downloads 314

Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

Procedia PDF Downloads 181

Authors: Khaled M. El Naggar

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This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

Procedia PDF Downloads 370

Authors: Aravind G., Arshinder Kaur, Pushpavanam S.

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There is a strong emphasis on shifting to electric vehicles (EVs) throughout the globe for reducing the impact on global warming following the Paris climate accord. Lithium-ion batteries (LIBs) are predominantly used in EVs, and these can be a significant threat to the environment if not disposed of safely. Lithium is also a valuable resource not widely available. There are several research groups working on developing an efficient recycling process for LIBs. Two routes - pyrometallurgical and hydrometallurgical processes have been proposed for recycling LIBs. In this paper, we focus on life cycle assessment (LCA) as a tool to quantify the environmental impact of these recycling processes. We have defined the boundary of the LCA to include only the recycling phase of the end-of-life (EoL) of the battery life cycle. The analysis is done assuming ideal conditions for the hydrometallurgical and a combined hydrometallurgical and pyrometallurgical process in the inventory analysis. CML-IA method is used for quantifying the impact assessment across eleven indicators. Our results show that cathode, anode, and foil contribute significantly to the impact. The environmental impacts of both hydrometallurgical and combined recycling processes are similar across all the indicators. Further, the results of LCA are used in developing a multi-objective optimization model for the design of lithium-ion battery recycling network. Greenhouse gas emissions and cost are the two parameters minimized for the optimization study.

Keywords: life cycle assessment, lithium-ion battery recycling, multi-objective optimization, network design, reverse supply chain

Procedia PDF Downloads 120

Authors: Elham Kiyani, S. Mansour Vaezpour, Javad Tavakoli

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In this paper, we first introduce a new distance function in a linear space not necessarily endowed with a topology. The algebraic concepts of interior and closure are useful to study optimization problems without topology. So, we define Q-weak efficient solutions generated by the algebraic interior of a set Q, where Q is not necessarily convex. Studying nonconvex vector optimization is valuable since, for a convex cone K in topological spaces, we have int(K)=cor(K), which means that topological interior of a convex cone K is equal to the algebraic interior of K. Moreover, we used the scalarization technique including the distance function generated by the vectorial closure of a set to characterize these Q-weak efficient solutions. Scalarization is a useful approach for solving vector optimization problems. This technique reduces the optimization problem to a scalar problem which tends to be an optimization problem with a real-valued objective function. For instance, Q-weak efficient solutions of vector optimization problems can be characterized and computed as solutions of appropriate scalar optimization problems. In the convex case, linear functionals can be used as objective functionals of the scalar problems. But in the nonconvex case, we should present a suitable objective function. It is the aim of this paper to present a new distance function that be useful to obtain sufficient and necessary conditions for Q-weak efficient solutions of general optimization problems via scalarization.

Keywords: weak efficient, algebraic interior, vector closure, linear space

Procedia PDF Downloads 193

Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

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The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: Samia Sadouki Chibani, Abdelkamel Tari

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Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.

Keywords: bio-inspired algorithms, elephant herding optimization, QoS optimization, web service composition

Procedia PDF Downloads 293

Authors: Mohammed Mohsin Ali H., Mohamed Haneef

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The connecting rod transmits the piston load to the crank causing the latter to turn, thus converting the reciprocating motion of the piston into a rotary motion of the crankshaft. Connecting rods are subjected to forces generated by mass and fuel combustion. This study investigates and compares the fatigue behavior of forged steel, powder forged and ASTM a 514 steel cold quenched connecting rods. The objective is to suggest for a new material with reduced weight and cost with the increased fatigue life. This has entailed performing a detailed load analysis. Therefore, this study has dealt with two subjects: first, dynamic load and stress analysis of the connecting rod, and second, optimization for material, weight and cost. In the first part of the study, the loads acting on the connecting rod as a function of time were obtained. Based on the observations of the dynamic FEA, static FEA, and the load analysis results, the load for the optimization study was selected. It is the conclusion of this study that the connecting rod can be designed and optimized under a load range comprising tensile load and compressive load. Tensile load corresponds to 360^o crank angle at the maximum engine speed. The compressive load is corresponding to the peak gas pressure. Furthermore, the existing connecting rod can be replaced with a new connecting rod made of ASTM a 514 steel cold quenched that is 12% lighter and 28% cheaper.

Keywords: connecting rod, ASTM a514 cold quenched material, static analysis, fatigue analysis, stress life approach

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Authors: Benmoussa Dennai, H. Benslimane, A. Helmaoui

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Photo voltaic conversion is the direct conversion of electromagnetic energy into electrical energy continuously. This electromagnetic energy is the most solar radiation. In this work we performed a computer modelling using AMPS 1D optimization of hetero-junction solar cells GaInP/GaAs configuration for p/ n. We studied the influence of the thickness the base layer in the cell offers on the open circuit voltage, the short circuit current and efficiency.

Keywords: optimization, photovoltaic cell, GaInP / GaAs AMPS-1D, hetetro-junction

Procedia PDF Downloads 372

Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

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This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: building's energy, control system, energy management, energy storage, genetic optimization algorithm, greenhouse gases, modelling, renewable energy

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Authors: Mustafa Sengul, Enes Sahin, Sertac Arslan

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Pumpjets are one of the marine propulsion systems frequently used in underwater vehicles nowadays. The reasons for frequent use of pumpjet as a propulsion system are that it has higher relative efficiency at high speeds, better cavitation, and acoustic performance than its rivals. Pumpjets are composed of rotor, stator, and duct, and there are two different types of pumpjet configurations depending on the desired hydrodynamic characteristic, which are with accelerating and decelerating duct. Pumpjet with an accelerating channel is used at cargo ships where it works at low speeds and high loading conditions. The working principle of this type of pumpjet is to maximize the thrust by reducing the pressure of the fluid through the channel and throwing the fluid out from the channel with high momentum. On the other hand, for decelerating ducted pumpjets, the main consideration is to prevent the occurrence of the cavitation phenomenon by increasing the pressure of the fluid about the rotor region. By postponing the cavitation, acoustic noise naturally falls down, so decelerating ducted systems are used at noise-sensitive vehicle systems where acoustic performance is vital. Therefore, duct design becomes a crucial step during pumpjet design. This study, it is aimed to optimize the duct geometry of a decelerating ducted pumpjet for a highly speed underwater vehicle by using proper optimization tools. The target output of this optimization process is to obtain a duct design that maximizes fluid pressure around the rotor region to prevent from cavitation and minimizes drag force. There are two main optimization techniques that could be utilized for this process which are parameter-based optimization and gradient-based optimization. While parameter-based algorithm offers more major changes in interested geometry, which makes user to get close desired geometry, gradient-based algorithm deals with minor local changes in geometry. In parameter-based optimization, the geometry should be parameterized first. Then, by defining upper and lower limits for these parameters, design space is created. Finally, by proper optimization code and analysis, optimum geometry is obtained from this design space. For this duct optimization study, a commercial codedparameter-based optimization algorithm is used. To parameterize the geometry, duct is represented with b-spline curves and control points. These control points have x and y coordinates limits. By regarding these limits, design space is generated.

Keywords: pumpjet, decelerating duct design, optimization, underwater vehicles, cavitation, drag minimization

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Authors: Mohammad Reza Ramezani, Shahriyar Afandizadeh

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Since the intersections play a crucial role in traffic delay, it is significant to evaluate them precisely. In this paper, three critical intersections in Tehran (Capital of Iran) had been simulated. The main purpose of this paper was to optimize the public transit delay. The simulation had three different phase in three intersections of Tehran. The first phase was about the current condition of intersection; the second phase was about optimized signal timing and the last phase was about prioritized public transit access. The Aimsun software was used to simulate all phases, and the Synchro software was used to optimization of signals as well. The result showed that the implement of optimization and prioritizing system would reduce about 50% of delay for public transit.

Keywords: transit signal priority, intersection optimization, public transit, simulation

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Authors: Ju-Hong Lee, Ding-Chen Chung

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This paper deals with the optimal design of recursive doubly complementary (DC) digital filter design using a metaheuristic based optimization technique. Based on the theory of DC digital filters using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the phase response errors of the designed DAFs. To deal with the stability of the recursive DC filters during the design process, we can either impose some necessary constraints on the phases of the recursive DAFs. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a population based stochastic optimization approach. The resulting DC digital filters can possess satisfactory frequency response. Simulation results are presented for illustration and comparison.

Keywords: doubly complementary, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

Procedia PDF Downloads 649

Authors: Varsha V. Rohini, P. R. Shreya, B. Renukadevi

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In the web analytics the information delivery and the web usage is optimized and the analysis of data is done. The analytics is the measurement, collection and analysis of webpage data. Page statistics and user metrics are the important factor in most of the web analytics tool. This is the limitation of the existing tools. It does not provide design inputs for the optimization of information. This paper aims at providing an extension for the scope of web analytics to provide analysis and statistics of each segment of a webpage. The number of click count is calculated and the concentration of links in a web page is obtained. Its user metrics are used to help in proper design of the displayed content in a webpage by Vision Based Page Segmentation (VIPS) algorithm. When the algorithm is applied on the web page it divides the entire web page into the visual block tree. The visual block tree generated will further divide the web page into visual blocks or segments which help us to understand the usage of each segment in a page and its content. The dynamic web pages and deep web pages are used to extend the scope of web page segment analytics. Space optimization concept is used with the help of the output obtained from the Vision Based Page Segmentation (VIPS) algorithm. This technique provides us the visibility of the user interaction with the WebPages and helps us to place the important links in the appropriate segments of the webpage and effectively manage space in a page and the concentration of links.

Keywords: analytics, design optimization, visual block trees, vision based technology

Procedia PDF Downloads 238

Authors: Yossiri Ariyakul, Piyakiat Insom, Poonyawat Sangiamkulthavorn, Takamichi Nakamoto

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In this paper, the method of optimization algorithm for sensor network comprised of movable sensor nodes which can be used for odor source localization was proposed. A sensor node is composed of an odor sensor, an anemometer, and a wireless communication module. The odor intensity measured from the sensor nodes are sent to the processor to perform the localization based on optimization algorithm by which the odor source localization map is obtained as a result. The map can represent the exact position of the odor source or show the direction toward it remotely. The proposed method was experimentally validated by creating the odor source localization map using three, four, and five sensor nodes in which the accuracy to predict the position of the odor source can be observed.

Keywords: odor sensor, odor source localization, optimization, sensor network

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Authors: Ahmed Cherif Megri, HossamEldin ElSherif

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In a power plant, the header pipe plays a pivotal role in optimizing the performance of diverse systems by serving as a central conduit for the collection and distribution of steam within the plant. This paper investigates the significance of header pipes within power plant setups, highlighting their critical influence on reliability, efficiency, and the performance of the power plant as a whole. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint of power plant installations. In this paper, we initially developed a methodology designed for optimizing header shapes with the primary goal of reducing the usage of costly new alloy materials and lowering the overall maintenance operation expenses. Secondly, we conducted a case study based on an authentic header sourced from an operational power plant.

Keywords: shape optimization, header, power plant, inconel alloy, CFD, structural optimization

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Authors: Faisel Elramalli, Ibrahim Althomali Amjad Sabbagh, Dhananjay Tambe

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SPEC CPU benchmarks are used to evaluate the performance of CPUs on computer systems. In our project we are going to use SPEC CPU suite that contains several benchmarks running on two different compilers gcc and icc in different optimizations levels to evaluate the performance of a CPU. The motivation of this project is to find out which compiler and in which optimization level makes the CPU reaches the best performance. The results of that evaluation will help users of these compilers to choose the best compiler and optimization level that perform efficiently for their work. In other words, it will give users the best performance of the CPU while doing their works. This project is interesting since it will provide the method used to measure the performance of CPU and how different optimization levels of compilers can help achieve a higher performance. Moreover, it will give a good understanding of how benchmarks are used to evaluate a CPU performance. For the reader, in reality SPEC CPU benchmarks are used to measure the performance of new released CPUs to be compared to other CPUs.

Keywords: SPEC, CPU, GCC, ICC, copilers

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Authors: Seyedmahdi Mousavihashemi

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One of the most important subjects of interest in researches is 'improving' which result in various algorithms. In so many geometrical problems we are faced with target functions which should be optimized. In group practices, all the functions’ cooperation lead to convergence. In the study, the optimization algorithm of dense particles is used. Usage of the algorithm improves the given performance norms. The results reveal that usage of swarm algorithm for reinforced particles in designing state feedback improves the given performance norm and in optimized designing of multi-target state feedback controlling, the network will maintain its bearing structure. The results also show that PSO is usable for optimization of state feedback controllers.

Keywords: multi-objective, enhanced, feedback, optimization, algorithm, particle, design

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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Agriculture in the world falls within the main sources of economic and global needs, so care of crop is extremely important for owners and workers; one of the major causes of loss of product is the pest infection of different types of organisms. We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB"," ANSYS FLUENT"," XFoil " package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi- objective problems can be helpful for future developments. The program has 10 functions developed in MATLAB, these functions are related to each other to enable the development of design, and all these functions are controlled by the principal code "Master.m".

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, stability, vortex

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Authors: Eva Queheille, Franck Taillandier, Nadia Saiyouri

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Waste management has become a major issue in demolition works, because of its environmental impact (energy consumption, resource consumption, pollution…). However, improving waste management requires to take also into account the overall demolition process and to consider demolition main objectives (e.g. cost, delay). Establishing a strategy with these conflicting objectives (economic and environment) remains complex. In order to provide a decision-support for demolition companies, a multi-objective optimization model was developed. In this model, a demolition strategy is computed from a set of 80 decision variables (worker team composition, machines, treatment for each type of waste, choice of treatment platform…), which impacts the demolition objectives. The model has experimented on a real-case study (demolition of several buildings in France). To process the optimization, different optimization algorithms (NSGA2, MOPSO, DBEA…) were tested. Results allow the engineer in charge of this case, to build a sustainable demolition strategy without affecting cost or delay.

Keywords: deconstruction, life cycle assessment, multi-objective optimization, waste management

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

Procedia PDF Downloads 54

Authors: Benmoussa Dennai, H. Benslimane, A. Helmaoui

Abstract:

Photovoltaic conversion is the direct conversion of electromagnetic energy into electrical energy continuously. This electromagnetic energy is the most solar radiation. In this work we performed a computer modelling using AMPS 1D optimization of hetero-junction solar cells GaInP / GaAs configuration for p / n. We studied the influence of the thickness the base layer in the cell offers on the open circuit voltage, the short circuit current and efficiency.

Keywords: optimization, photovoltaic cell, GaInP / GaAs AMPS-1D, hetetro-junction

Procedia PDF Downloads 487

Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

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Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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Authors: R.M. Asyraf, A. Norazah, S.M. Khairuddin, B. Noraziah

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Designing a system at present requires a vital, challenging task; to ensure the design philosophy is maintained in economical ways. This paper perceived the value engineering (VE) approach applied in infrastructure works, namely stormwater drainage. This method is adopted in line as consultants have completed the detailed design. Function Analysis System Technique (FAST) diagram and VE job plan, information, function analysis, creative judgement, development, and recommendation phase are used to scrutinize the initial design of stormwater drainage. An estimated cost reduction using the VE approach of 2% over the initial proposal was obtained. This cost reduction is obtained from the design optimization of the drainage foundation and structural system, where the pile design and drainage base structure are optimized. Likewise, the design of the on-site detention tank (OSD) pump was revised and contribute to the cost reduction obtained. This case study shows that the VE approach can be an important tool in optimizing the design to reduce costs.

Keywords: value engineering, function analysis system technique, stormwater drainage, cost reduction

Procedia PDF Downloads 115

Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

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Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: dielectric analysis, electronic packages, epoxy molding compounds, transfer molding process

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Authors: Kenza Aida Amara, Bachir Djebbar

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We treat the two-dimensional bin packing problem which involves packing a given set of rectangles into a minimum number of larger identical rectangles called bins. This combinatorial problem is NP-hard. We propose a pretreatment for the oriented version of the problem that allows the valorization of the lost areas in the bins and the reduction of the size problem. A heuristic method based on the strategy first-fit adapted to this problem is presented. We present an approach of resolution by bee colony optimization. Computational results express a comparison of the number of bins used with and without pretreatment.

Keywords: bee colony optimization, bin packing, heuristic algorithm, pretreatment

Procedia PDF Downloads 596

Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

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Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

Procedia PDF Downloads 200

Authors: Payel Ghosh, Rama Chandra Pradhan, Sabyasachi Mishra

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Jamun (Syzygium cuminii L.) is one of the important indigenous minor fruit with high medicinal value. The jamun cultivation is unorganized and there is huge loss of this fruit every year. The perishable nature of the fruit makes its postharvest management further difficult. Due to the strong cell wall structure of pectin-protein bonds and hard seeds, extraction of juice becomes difficult. Enzymatic treatment has been commercially used for improvement of juice quality with high yield. The objective of the study was to optimize the best treatment method for juice extraction. Enzymes (Pectinase and Tannase) from different stains had been used and for each enzyme, best result obtained by using response surface methodology. Optimization had been done on the basis of physicochemical property, nutritional property, sensory quality and cost estimation. According to quality aspect, cost analysis and sensory evaluation, the optimizing enzymatic treatment was obtained by Pectinase from Aspergillus aculeatus strain. The optimum condition for the treatment was 44 ^oC with 80 minute with a concentration of 0.05% (w/w). At these conditions, 75% of yield with turbidity of 32.21NTU, clarity of 74.39%T, polyphenol content of 115.31 mg GAE/g, protein content of 102.43 mg/g have been obtained with a significant difference in overall acceptability.

Keywords: enzymatic treatment, Jamun, optimization, physicochemical property, sensory analysis

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Authors: Stojan Kravanja, Andrej Ivanič, Tomaž Žula

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This contribution focuses on structural optimization in civil engineering using mixed integer non-linear programming (MINLP). MINLP is characterized as a versatile method that can handle both continuous and discrete optimization variables simultaneously. Continuous variables are used to optimize parameters such as dimensions, stresses, masses, or costs, while discrete variables represent binary decisions to determine the presence or absence of structural elements within a structure while also calculating discrete materials and standard sections. The optimization process is divided into three main steps. First, a mechanical superstructure with a variety of different topology-, material- and dimensional alternatives. Next, a MINLP model is formulated to encapsulate the optimization problem. Finally, an optimal solution is searched in the direction of the defined objective function while respecting the structural constraints. The economic or mass objective function of the material and labor costs of a structure is subjected to the constraints known from structural analysis. These constraints include equations for the calculation of internal forces and deflections, as well as equations for the dimensioning of structural components (in accordance with the Eurocode standards). Given the complex, non-convex and highly non-linear nature of optimization problems in civil engineering, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied. This algorithm alternately solves subproblems of non-linear programming (NLP) and main problems of mixed-integer linear programming (MILP), in this way gradually refines the solution space up to the optimal solution. The NLP corresponds to the continuous optimization of parameters (with fixed topology, discrete materials and standard dimensions, all determined in the previous MILP), while the MILP involves a global approximation to the superstructure of alternatives, where a new topology, materials, standard dimensions are determined. The optimization of a convex problem is stopped when the MILP solution becomes better than the best NLP solution. Otherwise, it is terminated when the NLP solution can no longer be improved. While the OA/ER algorithm, like all other algorithms, does not guarantee global optimality due to the presence of non-convex functions, various modifications, including convexity tests, are implemented in OA/ER to mitigate these difficulties. The effectiveness of the proposed MINLP approach is demonstrated by its application to various structural optimization tasks, such as mass optimization of steel buildings, cost optimization of timber halls, composite floor systems, etc. Special optimization models have been developed for the optimization of these structures. The MINLP optimizations, facilitated by the user-friendly software package MIPSYN, provide insights into a mass or cost-optimal solutions, optimal structural topologies, optimal material and standard cross-section choices, confirming MINLP as a valuable method for the optimization of structures in civil engineering.

Keywords: MINLP, mixed-integer non-linear programming, optimization, structures

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

Procedia PDF Downloads 227