The application of a tabu search metaheuristic to the assembly line balancing problem

This paper describes the application of tabu search, a metaheuristic technique for optimization problems, to assembly line balancing problems. Four different versions of algorithms are developed. They all share the same tabu search strategy except that the first one uses the best improvement with task aggregation, the second one uses best improvement without task aggregation, the third one uses the first improvement with task aggregation, and the last one uses the first improvement without task aggregation. Computational experiments with these different search strategies have been performed for some assembly line problems from the open literature. The results show that tabu search performs extremely well. Except for a few cases, tabu search always finds optimal solutions.