Type-2 Assembly Line Balancing Using Reactive Tabu Search

Abstract

This study focusses on a two objective type-2 simple assembly line balancing problem. Its primary objective is minimizing the cycle time, or equivalently, maximizing the production rate of the line. Minimization of the workload imbalance among workstations is considered as the secondary objective. Since the problem is known to be intractable, a reactive tabu search algorithm is proposed for the solution. Although tabu search is a well-known meta-heuristic search procedure, based on the detailed literature survey, there is not a reactive tabu search algorithm to solve the investigated problem. Furthermore, the algorithm utilizes a sequence oriented solution representation which is usually applied by population heuristics such as genetic algorithms and differential evolution algorithms. The performance of the algorithm is tested on several benchmark problems taken from the open literature by comparing both objective values with those of previously developed four particle swarm optimization (PSO) algorithms and two multi-objective genetic algorithms (MOGA). The computational results show that the proposed approach presents a quite encouraging success over the existing meta-heuristics.