Nested Bi-level metaheuristic algorithms for cellular manufacturing systems considering workers’ interest

Due to the competitive nature of market and various products production requirements with short life cycles, cellular manufacturing systems have found a special role in environments. Creativity innovation are results mental effort workforces addition machinery parts allocation. Assignment workforce cells based on interest ability indices is tactical decision while cell formation strategic decision. To make correct decision, these two problems should be solved separately considering their impacts each other classically. For this reason, novel bi-level model designed decentralized decisions. Because importance minimizing voids exceptional element system, it considered as leader at first level assignment human resources follower second level. achieve product synergy among staff objective function level, increasing worker’s order cooperate too. Given NP-Hard programming, nested genetic algorithm particle swarm optimization developed solve mathematical model. Various test been by applying methods validated shown efficiency proposed Also, real experimental comparisons presented. These contrast previous works minimum amount computational time, load variation, total intercellular movements, intracellular movements new method. effects an important improvement behavior.