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Multi-objective meta-heuristics to solve three-stage assembly flow shop scheduling problem with machine availability constraints

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2015年第3期53卷 944-968页

作者： Shoaardebili, Niloofar Fattahi, Parviz Bu Ali Sina Univ Dept Ind Engn Hamadan Iran

In this paper, a three-stage assembly flow shop scheduling problem with machine availability constraints is taken into account. Two objectives of minimising total weighted completion times (flow time) and minimising sum of weighted tardiness and earliness are simultaneously considered. To describe this problem, a mathematical model is presented. The problem is generalisation of three-machine flow shop scheduling problemand two-stage assembly flow shop scheduling problem. Since these problems are known to be NP-hard, the considered problem is also strongly NP-hard. Therefore, two multi-objective meta-heuristics are presented to efficiently solve this problem in a reasonable amount of time. Comprehensive computational experiments are performed to illustrate the performance of the presented algorithms.

关键词： simulated annealing multi-objective optimisation assembly flow shop machine availability constraint non-dominated sorting genetic algorithm

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Multi-Objective Optimization Design for Indirect Forced-Circulation Solar Water Heating System Using NSGA-II

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ENERGIES 2015年第11期8卷 13137-13161页

作者： Ko, Myeong Jin Incheon Natl Univ Urban Dev Inst Inchon 406772 South Korea

In this study, the multi-objective optimization of an indirect forced-circulation solar water heating (SWH) system was performed to obtain the optimal configuration that minimized the life cycle cost (LCC) and maximized the life cycle net energy saving (LCES). An elitist non-dominated sorting genetic algorithm (NSGA-II) was employed to obtain the Pareto optimal solutions of the multi-objective optimization. To incorporate the characteristics of practical SWH systems, operation-related decision variables as well as capacity-related decision variables were included. The proposed method was used to conduct a case study wherein the optimal configuration of the SWH system of an office building was determined. The case study results showed that the energy cost decreases linearly and the equipment cost increases more significantly as the LCES increases. However, the results also showed that it is difficult to identify the best solution among the Pareto optimal solutions using only the correlation between the corresponding objective function values. Furthermore, regression analysis showed that the energy and economic performances of the Pareto optimal solutions are significantly influenced by the ratio of the storage tank volume to the collector area (RVA). Therefore, it is necessary to simultaneously consider the trade-off and the effect of the RVA on the Pareto optimal solutions while selecting the best solution from among the optimal solutions.

关键词： solar water heating system multi-objective optimization life cycle cost life cycle net energy saving non-dominated sorting genetic algorithm Pareto optimal solution

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Comparative Analog Circuit Design Automation Based on Multi-Objective Evolutionary algorithms: an Application on CMOS Opamp 38

Comparative Analog Circuit Design Automation Based on Multi-...

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38th International Conference on Telecommunications and Signal Processing (TSP)

作者： Canturk, Ismail Kahraman, Nihan Yildiz Tech Univ Istanbul Turkey

ISBN: (纸本)9781479984985

Automation of analog integrated circuit (IC) design process is very important because of the optimization contradictions. In this study, benefits of multi-objective evolutionary algorithms are presented on two stage operational amplifier design using Harmony Search algorithm (HSA) and non-dominated sorting genetic algorithm (NSGA-II). HSA is a new kind of multi-objective evolutionary algorithm which was inspired from the musicians those are looking for the best combination of musical sounds of different instruments that produces most pleasing sound. NSGA-II is an advanced version of genetic algorithm. It combines both current parents and their child population to select new parents. These kinds of design automation tools are required for analog circuit design because there are several contradictions in the design. In this work, transistor sizes which effects all constraints indirectly were automatically synthesized by HSA an NSGA-II.

关键词： Analog circuit automation computer-aided design harmony search algorithm non-dominated sorting genetic algorithm

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Multi-objective production-distribution planning based on vendor-managed inventory strategy in a supply chain

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INDUSTRIAL MANAGEMENT & DATA SYSTEMS 2015年第6期115卷 1086-1112页

作者： Niknamfar, Amir Hossein Islamic Azad Univ Young Researchers & Elite Club Qazvin Branch Qazvin Iran

Purpose - The production-distribution (P-D) problems are two critical problems in many industries, in particular, in manufacturing systems and the supply chain management. In previous researches on P-D planning, the demands of the retailers and their inventory levels have less been controlled. This may lead into huge challenges for a P-D plan such as the bullwhip effects. Therefore, to remove this challenge, the purpose of this paper is to integrate a P-D planning and the vendor-managed inventory (VMI) as a strong strategy to manage the bullwhip effects in supply chains. The proposed P-D-VMI aims to minimize the total cost of the manufacturer, the total cost of the retailers, and the total distribution time simultaneously. Design/methodology/approach - This paper presents a multi-objective non-linear model for a P-D planning in a three-level supply chain including several external suppliers at the first level, a single manufacturer at the second level, and multi-retailer at the third level. A non-dominated sorting genetic algorithm and a non-dominated ranking genetic algorithm are designed and tuned to solve the proposed problem. Then, their performances are statistically analyzed and ranked by the TOPSIS method. Findings - The applicability of the proposed model and solution methodologies are demonstrated under several problems. A sensitivity analysis indicates the market scale and demand elasticity have a substantial impact on the total cost of the manufacturer in the proposed P-D-VMI. Originality/value - Although the P-D planning is a popular approach, there has been little discussion about the P-D planning based on VMI so far. The novelty comes from developing a practical and new approach that integrates the P-D planning and VMI.

关键词： Supply chain management non-dominated sorting genetic algorithm Production-distribution planning Vendor-managed inventory

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Performance-based multi-objective optimal design of steel frame structures: nonlinear dynamic procedure

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SCIENTIA IRANICA 2015年第2期22卷 373-387页

作者： Kaveh, A. Fahimi-Farzam, M. Kalateh-Ahani, M. Iran Univ Sci & Technol Ctr Excellence Fundamental Studies Struct Engn Tehran Iran

The main problem in performance-based structures is the extremely high computational demand of time-history analyses. In this paper, an efficient framework is developed for solving the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. For improving the time efficiency of the solution algorithm, the Generalized Regression Neural Network (GRNN) is utilized as the meta-model for fitness approximation, and a specific evolution control scheme is developed. In this scheme, in order to determine which individuals should be evaluated using the original fitness function and which by the meta-model, the Fuzzy C-Mean (FCM) clustering algorithm is used to choose the competent individuals rather than choosing the individuals randomly. Moreover, the computational burden of time history analyses is decreased through a particular wavelet analysis procedure. The constraints of the optimization problem are considered in accordance with the FEMA codes. The results obtained from numerical application of the proposed framework demonstrate its capabilities in solving the present multi-objective optimization problem. (C) 2015 Sharif University of Technology. All rights reserved.

关键词： Performance-based design nonlinear dynamic analysis Steel frame structures Seismic damage cost non-dominated sorting genetic algorithm Generalized regression neural network Fuzzy c-mean clustering Wavelet analysis

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Comparative Analog Circuit Design Automation Based on Multi-Objective Evolutionary algorithms: an Application on CMOS Opamp

Comparative Analog Circuit Design Automation Based on Multi-...

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International Conference on Telecommunications and Signal Processing

作者： Ismail Canturk Nihan Kahraman Yildiz Technical University

ISBN: (纸本)9781479984992

关键词： Analog circuit automation Computer-aided design Harmony search algorithm non-dominated sorting genetic algorithm

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THERMAL-ECONOMIC MULTI-OBJECTIVE OPTIMIZATION OF HEAT PIPE HEAT EXCHANGER FOR ENERGY RECOVERY IN HVAC APPLICATION USING genetic algorithm

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THERMAL SCIENCE 2014年第Sup2期18卷 S375-S391页

作者： Sanaye, Sepehr Modarrespoor, Davood Iran Univ Sci & Technol Dept Mech Engn Energy Syst Improvement Lab Tehran Iran

Cost and effectiveness are two important factors of heat pipe heat exchanger design. The total cost includes the investment cost for buying equipment (heat exchanger surface area) and operating cost for energy expenditures (related to fan power). The heat pipe heat exchanger was thermally modeled using epsilon-NTU method to estimate the overall heat transfer coefficient for the bank of finned tubes as well as estimating pressure drop. Fast and elitist non-dominated sorting genetic algorithm II with continuous and discrete variables was applied to obtain the maximum effectiveness and the minimum total cost as two objective *** diameter, pipe length, numbers of pipes per row, number of rows, fin pitch and fin lengthratio were considered as six design parameters. The results of optimal designs were a set of multiple optimum solutions, called "Pareto optimal solutions". The comparison of the optimum values of total cost and effectiveness, variation of optimum values of design parameters as well as estimating the payback period were also reported for various inlet fresh air volume flow rates.

关键词： heat pipe heat exchanger heat recovery effectiveness total cost multi-objective optimization non-dominated sorting genetic algorithm

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A bi-objective optimization approach for exclusive bus lane selection and scheduling design

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ENGINEERING OPTIMIZATION 2014年第7期46卷 987-1007页

作者： Khoo, Hooi Ling Teoh, Lay Eng Meng, Qiang Univ Tunku Abdul Rahman UTAR Fac Sci & Engn Dept Civil Engn Kuala Lumpur Malaysia Univ Tunku Abdul Rahman UTAR Fac Sci & Engn Dept Math & Actuarial Sci Kuala Lumpur Malaysia Natl Univ Singapore Fac Engn Dept Civil & Environm Engn Singapore 117548 Singapore

This study proposes a methodology to solve the integrated problems of selection and scheduling of the exclusive bus lane. The selection problem intends to determine which roads (links) should have a lane reserved for buses while the scheduling problem intends to find the time period of the application. It is formulated as a bi-objective optimization model that aims to minimize the total travel time of non-bus traffic and buses simultaneously. The proposed model formulation is solved by the hybrid non-dominated sorting genetic algorithm with Paramics. The results show that the proposed methodology is workable. Sets of Pareto solutions are obtained indicating that a trade-off between buses and non-bus traffic for the improvement of the bus transit system is necessary when the exclusive bus lane is applied. This allows the engineer to choose the best solutions that could balance the performance of both modes in a multimode transport system environment to achieve a sustainable transport system.

关键词： bi-objective optimization exclusive bus lane Pareto solution non-dominated sorting genetic algorithm

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Life-cycle cost optimization of steel moment-frame structures: performance-based seismic design approach

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EARTHQUAKES AND STRUCTURES 2014年第3期7卷 271-294页

作者： Kaveh, A. Kalateh-Ahani, M. Fahimi-Farzam, M. Iran Univ Sci & Technol Ctr Excellence Fundamental Studies Struct Engn Tehran 16844 Iran

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem;first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

关键词： performance-based design nonlinear dynamic analysis steel moment-frame structure life-cycle cost non-dominated sorting genetic algorithm simplified nonlinear modeling wavelet analysis

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A New Bi-objective Mathematical Model for Sustainable Dynamic Cellular Manufacturing Systems

A New Bi-objective Mathematical Model for Sustainable Dynami...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Niakan, F. Baboli, A. Moyaux, T. Botta-Genoulaz, V. Univ Lyon INSA Lyon DISP EA4570 F-69621 Villeurbanne France

ISBN: (纸本)9781479964109

This study addresses dynamic cell configuration and labor assignment by making a trade-off between economic, social and environmental criteria which is called as sustainability configuration. In order to improve the study about energy loss, a new bi-objective mathematical model is presented. The first objective of model minimizes cost criteria and the second one energy loss which is represented by the efficiency of each machine. We develop a non-dominated sorting genetic algorithm (NSGA-II) in order to solve our model. The applicability of our approach is illustrated by two test problems.

关键词： Dynamic cell configuration sustainability bi-objective optimization non-dominated sorting genetic algorithm

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