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Stochastic design optimization of asynchronous flexible assembly systems

  • II. Design Problems
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Abstract

This paper presents the application of the stochastic quasigradient method (SQG) of Ermoliev and Gaivaronski to the performance optimization of asynchronous flexible assembly systems (AFAS). These systems are subject to blocking and starvation effects that make complete analytic performance modeling difficult. A hybrid algorithm is presented in this paper which uses a queueing network model to set the number of pallets in the system and then an SQG algorithm is used to set the buffer spacings to obtain optimal system throughput. Different forms of the SQG algorithm are examined and the specification of optimal buffer sizes and pallet numbers for a variety of assembly systems with ten stations are discussed. The combined Network-SQG method appears to perform well in obtaining a near optimal solution in this discrete optimization example, even though the SQG method was primarily designed for application to differentiable performance functionals. While a number of both theoretical and practical problems remain to be resolved, a heuristic version of the SQG method appears to be a reasonable technique for analyzing optimization problems for certain complex manufacturing systems.

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Authors and Affiliations

  1. Department of Industrial Engineering, National Tsing Hua University, Taiwan

    Chih-Ming Liu

  2. Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Avenue, 53706, Madison, Wisconsin, USA

    Jerry L. Sanders

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  1. Chih-Ming Liu
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  2. Jerry L. Sanders
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Liu, CM., Sanders, J.L. Stochastic design optimization of asynchronous flexible assembly systems. Ann Oper Res 15, 131–154 (1988). https://doi.org/10.1007/BF02186794

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