Multiple-colony ant algorithm for parallel assembly line balancing problem

Assembly lines are designed as flow oriented production systems which perform operations on standardized products in a serial manner. Balancing of assembly lines is one of the most important problems among the other problems of assembly lines like designing and managing. In today's highly competitive manufacturing environment increasing system flexibility, reducing failure sensitivity, improving system balance and productivity are crucial. Parallel assembly lines provide some opportunities in improving these objectives especially when the capacity of production system is insufficient. Unlike the traditional assembly lines there are a few studies on balancing parallel assembly lines in the present literature. Parallel assembly line balancing is a NP-hard problem similar to other assembly lines. In this paper, a novel multiple-colony ant algorithm is developed for balancing bi-objective parallel assembly lines. The proposed algorithm is also one of the first attempts in modeling and solving the present problem with swarm intelligence based meta-heuristics. The proposed approach is extensively tested on the benchmark problems and performance of the approach is compared with existing algorithms. It is shown that the proposed approach is very effective.