A hybrid algorithm proposal for solving general assembly line balancing problems with sequence-dependent setup times

Many studies have been conducted in the literature on Simple Assembly Line Balancing Problems (SALBP). However, there was a huge gap between academic studies and industry practices due to the limitations found in SALBP. In order to close this gap, studies under the field of the General Assembly Line Balancing Problems (GALBP) have been started to solve the practical problems of the industry. The sequence-dependent setup times, which are common in the automotive and electronics sectors, have not been addressed in previous Assembly Line Balancing (ALB) studies. Setup times were added to station times to solve the problems in previous ALB studies. As this approach is insufficient to solve the problem, the sequence-dependent setup times GALBP studies have emerged. Because the sequence-dependent setup times GALBP is NP-hard and very complex problems, they can not be solved in reasonable time by deterministic methods such as linear programming and branch and bound algorithm. In this study, a new Differential Evolution Algorithm (DEA) and Differential Evolution Algorithm (DEA) - Particle Swarm Optimization (PSO) Hybrid Algorithm (HA) which are metaheuristics, was developed to solve these problems. The performance of the developed DGA and HA was tested on the test problems in the literature and they gave better results than the previously developed heuristic methods in the literature.