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BI-CRITERIA SCHEDULING ON A BATCHING MACHINE WITH NON-IDENTICAL JOB SIZES

IFAC Proceedings Volumes 2006年第3期39卷 727-732页

作者： Ali Husseinzadeh Kashan Behrooz Karimi Fariborz Jolai Department of Industrial Engineering Amirkabir University of Technology P.O.Box: 15875-4413 Tehran Iran Department of Industrial Engineering Faculty of Engineering University of Tehran P.O.Box: 11365-4563 Tehran Iran

This paper addresses scheduling jobs with non-identical sizes on a single batch-processing machine. Two different multi-objective genetic algorithms (MOGA) have been proposed. The first one is a sequence based MOGA (SMOGA) that generates random sequences of jobs and applies the batch first fit heuristic to group the jobs. The second one is a batch based hybrid MOGA (BHMOGA) that generates random batches of jobs and ensures feasibility through using knowledge of the problem. Computational results show that non-dominated solutions obtained by BHMOGA are superior in closeness to the true Pareto-optimal solutions and to keep diversity in the obtained Pareto-set, as the problem size increases.

关键词： Scheduling Batch processing machine multi-objective genetic algorithm Makespan Maximum tardiness

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multi-objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions

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TIRE SCIENCE AND TECHNOLOGY 2006年第3期34卷 170-194页

作者： Koishi, M. Shida, Z. Yokohama Rubber Co Ltd 2-1 Oiwake Hiratsuka Kanagawa 2548601 Japan

Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called "multi-performan

关键词： inverse problem multi-objective optimization multi-objective genetic algorithm self-organizing map Pareto solution wear finite element analysis

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A new method to construct the non-dominated set in multi-objective genetic algorithms

A new method to construct the non-dominated set in multi-obj...

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2nd International Conference on Intelligent Information Processing

作者： Zheng, JH Shi, ZZ Ling, CX Xie, Y Xiangtan Univ Coll Informat Engn Xiangtan 411105 Peoples R China

ISBN: (纸本)038723151X

There have been widespread applications for multi objective genetic algorithm (MOGA) on highly complicated optimization tasks in discontinuous, multi-modal, and noisy domains. Because the convergence of MOGA can be reached with the non-dominated set approximating the Pareto Optimal front, it is very important to construct the non-dominated set of MOGA efficiently. This paper proposes a new method called Dealer's Principle to construct non-dominated sets of MOGA, and the time complexity is analyzed. Then we design a new MOGA with the Dealer's Principle and a clustering algorithm based on the core distance of clusters to keep the diversity of solutions. We show that our algorithm is more efficient than the previous algorithms, and that it produces a wide variety of solutions. We also discuss the convergence and the diversity of our MOGA in experiments with benchmark optimization problems of three objectives.

关键词： multi-objective genetic algorithm multi-objective optimum dominated relationship non-dominated set

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An Improved genetic algorithm for multi-objective Optimization

An Improved Genetic Algorithm for Multi-objective Optimizati...

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智能计算及其应用国际会议

作者： CHEN Guolong1,2, GUO Wenzhong1, TU Xuezhu1, CHEN Huowang2 (1. Institute of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002 , China) (2. School of Computer Science, National University of Defense Technology, Changsha 410073, China)

This paper describes a non-generational GA for multi-objective optimization problems (MOP) based on a crossover operator called DC (Dislocation Crossover). In it the replacement policy is such that an

关键词： multi-objective genetic algorithm dislocation crossover multi-objective optimization non-dominated solutions

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Introducing more choices (flexibility) in the upgrading of water distribution networks: the New York city tunnel network example

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ENGINEERING OPTIMIZATION 2005年第3期37卷 291-305页

作者： Khu, ST Keedwell, E Univ Exeter Sch Engn Comp Sci & Math Ctr Water Syst Exeter EX4 4QF Devon England

The New York city tunnel network problem is a classical case study for water distribution network rehabilitation or upgrading. However, standard problem formulations only offer single solutions based on fixed pressure head and demand requirements. This problem is re-examined through the use of multiple criteria optimization and a framework for interpreting these results is proposed. Results from previous studies were closely examined to highlight areas that can be improved. A 6-objective optimization problem was then formulated and results were compared with optimization using a single-objective genetic algorithm (GA) and 2-objectives optimization using a non-dominated sorted genetic algorithm-II. Although the initial runtime for the 6-objective optimization was long compared with single-objective GA, it provided solutions which span the whole spectrum of possibilities ( in terms of pressure head requirements and cost). It is concluded that the proposed 6-objectives formulation can indeed offer more design choices, hence flexibility, for designers and decision makers.

关键词： water distribution system rehabilitation upgrading multi-objective genetic algorithm

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Design for product-embedded disassembly with maximum profit

Design for product-embedded disassembly with maximum profit

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4th International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign 05)

作者： Takeuchi, Shingo Saitou, Kazuhiro Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

ISBN: (纸本)1424400813

This paper describes an extension of a method for designing products with built-in disassembly means developed in our previous work, as applied to a realistic example of a desktop computer assembly. Given component geometries and revenues, the method simultaneously determines, through an optimization process, the spatial configuration of component, locator and fasteners such that the product can be most economically disassembled via a domino-like "self-disassembly" process triggered by the removal of one or a few fasteners. A multi-objective genetic algorithm is utilized to search for Pareto-optimal designs in terms Of four objectives: 1) satisfaction of the distance specification among components, 2) efficient use of locators on components, 3) profit of overall disassembly process, and 4) mass fraction of retrieved components. The method is applied to a simplified model of Power Mac G4 cube (R), and the results inspired a modification to the current design that can improve the ease of disassembly.

关键词： design for disassembly configuration design disassembly sequence planning multi-objective genetic algorithm

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multi-objective optimization of diesel engine emissions and fuel economy using SPEA2+ 05

Multi-objective optimization of diesel engine emissions and ...

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genetic and Evolutionary Computation Conference

作者： Hiroyasu, Tomoyuki Miki, Mitsunori Nakayama, Seiichi Hanada, Yoshiko Doshisha Univ Kyoto Japan

No abstract available.

ISBN: (纸本)1595930108

No abstract available.

关键词： design multi-objective genetic algorithm automobile industry

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Cell formation using modular-reconfigurable machines

Cell formation using modular-reconfigurable machines

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16th International Symposium of the Danube-Adria-Association-for-Automation-and-Manufacturing

作者： Pattanaik, L. N. Jain, P. K. Mehta, N. K.

ISBN: (纸本)9783901509469

In this research, an approach is made to design machine cells using modular-reconfigurable machines to achieve certain characteristics of reconfigurable manufacturing. Each machine considered in the model consists of some basic and auxiliary machine modules. By changing the auxiliary modules, different operations can be performed on the machines. A similarity measure among machines based on production flow information and auxiliary module requirement is developed. Machine cells are identified using a multi-objective evolutionary genetic algorithm for a set of parts with parameters like volumes of production, alternative operation based process plans etc. The two objectives considered are minimization of inter-cell movement and total changes in auxiliary modules for the given production horizon. An illustrative problem and experimental results are given.

关键词： cell formation modular-reconfigurable machines multi-objective genetic algorithm

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Design for product-embedded disassembly pathways

Design for product-embedded disassembly pathways

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IEEE International Conference on Automation Science and Engineering

作者： Takeuchi, S Saitou, K Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

ISBN: (纸本)0780394259

This paper presents a computational method for designing an assembly with multiple built-in disassembly pathways, each of which can be activated to retrieve certain components. It is motivated by the global sales of consumer products whose optimal end-of-life options vary geographically due to local recycling/reuse infrastructures and regulatory requirements. Given the sets of components to be retrieved at each location, the method simultaneously determines the spatial configurations of components and locator features, such that each set of desired components is retrieved via a domino-like "self-disassembly" process triggered by the removal of a fastener. A multi-objective generic algorithm is utilized to search for Pareto-optimal designs in terms of the realization of the desired disassembly pathways, the satisfaction of distance specifications among components, the minimization of disassembly cost at each location, and the efficient use of oncomponent locator features. A case study demonstrates the feasibility of the method.

关键词： design for disassembly computer aided design product design automation multi-objective genetic algorithm

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Dynamic power minimization during combinational circuit testing as a traveling salesman problem

Dynamic power minimization during combinational circuit test...

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IEEE Congress on Evolutionary Computation

作者： Sokolov, A Sanyal, A Whitley, D Malaiya, Y Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)0780393635

Testing of VLSI circuits can cause generation of excessive heat which can damage the chips under test. In the random testing environment, high-performance CMOS circuits consume significant dynamic power during testing because of enhanced switching activity in the internal nodes. Our work focuses on the fact that power minimization is a Traveling Salesman Problem (TSP). We explore application of local search and genetic algorithms to test set reordering and perform a quantitative comparison to previously used deterministic techniques. We also consider reduction of the original test set as a dual-objective optimization problem, where switching activity and fault coverage are the two objective functions.

关键词： combinational circuit testing test vector automatic test pattern generator (ATPG) fault coverage traveling salesman problem (TSP) genetic algorithm application weight-biased edge crossover multi-objective genetic algorithm

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