Multi-Objective Cellular Manufacturing Metaheuristics: Review Paper

Cellular Manufacturing (CM) is a GT component defined as a production system in which related components are categorized as part families, and parts that need comparable manufacturing techniques are separated into different manufacturing cells. This study thoroughly reviews the literature on cell formation issues in cellular manufacturing systems for multi-objective problems solved with various heuristics and metaheuristics. It also specifies the objectives, production parameters, and data sets used to evaluate the effectiveness of algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and other current algorithms are discussed in this work, as well as tabu search, simulated annealing, and other heuristics and metaheuristic algorithms. GA has been considered 54%, SA 20%, ACO 8%, PSO 7%, TS 6%, and 5% for other algorithms from the published work. Future research topics are suggested to include labor assignment, uncertainty in component and machine efficiency, and demand changes.