Title: Performance comparison of search-based simulation optimisation algorithms for operations scheduling

Authors: Mohammed Jafferali, Jayendran Venkateshwaran, Young-Jun Son

Addresses: Systems and Industrial Engineering Department, Engineering Building No. 20, Room No. 111, The University of Arizona, Tucson, AZ 85721, USA. ' Systems and Industrial Engineering Department, Engineering Building No. 20, Room No. 111, The University of Arizona, Tucson, AZ 85721, USA. ' Systems and Industrial Engineering Department, Engineering Building No. 20, Room No. 111, The University of Arizona, Tucson, AZ 85721, USA

Abstract: This paper discusses the use of meta-heuristics coupled with discrete event simulations of various manufacturing systems to find the optimal operation schedules. Two search-based heuristic algorithms, OptQuest® (based on scatter search, tabu search and neural networks) and SimRunner® (based on genetic algorithm), are compared with respect to the quality of results and the computational time for a family of manufacturing system problems. The set of manufacturing systems configurations have been defined using the factors ||type of shop|| (flow shop and job shop), ||number of part types|| and ||number of machines||. This family of problems is analysed based on the stochasticity of data, which is, using either deterministic or stochastic data for part inter-arrival times and processing times. A structured experiment has been conducted to test the responses of the two algorithms in optimising two different objective functions, maximising throughput rate and minimising percentage of tardy jobs. Arena® embedding OptQuest® and ProModel® embedding SimRunner® have been used in this research. Significant validation efforts have been made to ensure that simulation models built in Arena® and ProModel® are identical so that the performance difference only accrues from the heuristics. Evidences have been found to indicate that SimRunner® produced better results when the computation time is limited; however, OptQuest® produced comparable, sometimes superior results, when allowed infinite computation time.

Keywords: simulation optimisation; operations scheduling; discrete event simulation; metaheuristics; performance comparison; experimental design; OptQuest; SimRunner; ANOVA; manufacturing siumlation; tabu search; neural networks; genetic algorithms; throughput rate; tardy jobs; process modelling; scheduling simulation.

DOI: 10.1504/IJSPM.2005.007114

International Journal of Simulation and Process Modelling, 2005 Vol.1 No.1/2, pp.58 - 71

Published online: 27 May 2005 *

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