Using Multi-objective Genetic Algorithm with Fuzzy Logic Controller for Assembly Line Balancing Problem with Worker Allocation

Assembly lines are typical flow oriented production systems, which are of great importance in the industrial production of high quantity standardized commodities. The assembly line balancing (ALB) problems deal with the assignment of various tasks to an ordered sequence of workstations, while opti-mizing one or more objectives without violating restrictions imposed on the line. In this study, we formulated the mathematical model for ALB problem with worker allocation. Later we proposed a random key-based genetic algorithm (rkGA) to solve this problem. Moreover, we presented an auto-tuning strategy, which adopts fuzzy logic controller (FLC) to tune the probabilities of the genetic operators. Finally, in order to evaluate the effectiveness of the proposed approach, we made several computational experiments using various ALB problems. The results indicated that the pro-posed approach improved quality of solutions and enhanced rate of convergence more than the other existing GA approaches