An ant colony optimization algorithm for load balancing in parallel machines with sequence-dependent setup times

Authors:
Timur Keskinturk;Mehmet B. Yildirim;Mehmet Barut
Affiliations:
Department of Quantitative Methods, Faculty of Business Administration, Istanbul University, Istanbul 34320, Turkey;Department of Industrial and Manufacturing Engineering, Wichita State University, Wichita, KS 67260, USA;Department of Finance, Real Estate, and Decision Sciences, Barton School of Business, Wichita State University, Wichita, KS 67260, USA
Venue:
Computers and Operations Research
Year:
2012

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Abstract

This study introduces the problem of minimizing average relative percentage of imbalance (ARPI) with sequence-dependent setup times in a parallel-machine environment. A mathematical model that minimizes ARPI is proposed. Some heuristics, and two metaheuristics, an ant colony optimization algorithm and a genetic algorithm are developed and tested on various random data. The proposed ant colony optimization method outperforms heuristics and genetic algorithm. On the other hand, heuristics using the cumulative processing time obtain better results than heuristics using setup avoidance and a hybrid rule in assignment.