Metaheuristic optimization in solving assembly line balancing problems: A short review

Recently assembly line balancing (ALB) is an ultimate focus issue in manufacturing industries for optimizing both common goals which were the number of workstations and the production rate. Metaheuristic is one of optimization problem-independent technique. This paper focusses on the short review of metaheuristic optimization in solving assembly line balancing problems. Hence, to produce a summary of the review, this paper selects some publications for the past 3 years from year 2016 to 2019. From the review shows the metaheuristic optimization that often used are Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Differential Evaluation (DE), Evolutionary Algorithm (EA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). Besides, GA is most frequently used to solve ALB problems. Finally, recommendation for future research for solving ALB Problems using metaheuristic optimization are discussed.