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.

This is the author's version of the proceedings article written for 13th IFAC Symposium on Information Control Problems in Manufacturing (INCOM) held in June 03-05, 2009, Moscow Russia. It is posted here by permission of Elsevier for personal use, not for redistribution. Accepted for publications to Computers & Operations Research,v.37 Dec. doi:10.1016/j.cor.2010.12.003