A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles

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Abstract

This article addresses the problem of simultaneous scheduling of machines and a number of identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS) so as t minimize the makespan. For solving this problem, a genetic algorithm (GA) is proposed. Here, chromosomes represent both operation sequencing and AGV assignment dimensions of the search space. A third dimension, time, is implicitly given by the ordering of operations of the chromosomes. A special uniform crossover operator is developed which produces one offspring from two parent chromosomes. It transfers any patterns of operation sequences and/or AGV assignments that are present in both parents to the child. Two mutation operators are introduced; a bitwise mutation for AGV assignments and a swap mutation for operations. Any precedence infeasibility resulting from the operation swap mutation is removed by a repair function. The schedule associated with a given chromosome is determined by a simple schedule builder. After a number of problems are solved to evaluate various search strategies and to tune the parameters of the proposed GA, 180 test problems are solved to evaluate various search lower bound is introduced and compared with the results of GA. In 60% of the problems GA reaches the lower bound indicating optimality. The average deviation from the lower bound over all problems is found to be 2.53%. Additional comparison is made with the time window approach suggested for this same problem using 82 test problems from the literature. In 59% of the problems GA outperforms the time window approach where the reverse is true only in 6% of the problems.

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  • Cited by (0)

    Gündüz Ulusoy is Professor of Industrial Engineering at Boǧaziçi University, Istanbul. He received his BSME from Robert College, Istanbul; MSME from University of Rochester and PhD from VPI&SU. His current research focuses on advanced manufacturing systems and project and machine scheduling. He is currently an Associate Editor of the European Journal of Operational Research. He has published research articles in Interface, Journal of the Operational Research Society, European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, IIE Transactions, International Journal of Production and Operations Management, Journal of Operations Management.

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    Funda Sivrikaya-Serifoǧlu is a doctoral student in the Department of Industrial Engineering at Boǧaziçi University, Istanbul. She holds a B.S. degree in Industrial Engineering from that university and an M.S. degree in Engineering Economic Systems from Stanford University. She is currently conducting doctoral research in genetic algorithm applications in machine and project scheduling.

    Ümit Bilge is an Assistant Professor of Industrial Engineering at Boǧaziçi University, Istanbul. Her research interests include design and analysis of computer integrated manufacturing systems, flexible manufacturing systems, automated guided vehicle systems, manufacturing information systems and production planning and control. Dr. Bilge has published in Operations Research and International Journal of Production Research.

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