An archived multi-objective simulated annealing for a dynamic cellular manufacturing system

To design a group layout of a cellular manufacturingsystem (CMS) in a dynamic environment, amulti-objective mixed-integer non-linear programmingmodel is developed. The model integrates cell formation,group layout and production planning (PP) as three interrelateddecisions involved in the design of a CMS. Thispaper provides an extensive coverage of important manufacturingfeatures used in the design of CMSs and enhancesthe flexibility of an existing model in handling the fluctuationsof part demands more economically by addingmachine depot and PP decisions. Two conflicting objectivesto be minimized are the total costs and the imbalanceof workload among cells. As the considered objectives inthis model are in conflict with each other, an archivedmulti-objective simulated annealing (AMOSA) algorithmis designed to find Pareto-optimal solutions. Matrix-basedsolution representation, a heuristic procedure generating aninitial and feasible solution and efficient mutation operatorsare the advantages of the designed AMOSA. To demonstratethe efficiency of the proposed algorithm, the performanceof AMOSA is compared with an exact algorithm(i.e., [-constraint method) solved by the GAMS softwareand a well-known evolutionary algorithm, namely NSGAIIfor some randomly generated problems based on somecomparison metrics. The obtained results show that thedesigned AMOSA can obtain satisfactory solutions for themulti-objective model.