Abstract
Cellular manufacturing (CM) is an important application of group technology (GT) in which families of parts are produced in manufacturing cells or in a group of various machines. Cell design/formation is the first step in the design of cellular manufacturing systems. Many efforts have been made towards cell design taking into consideration multiple criteria. This paper presents a Pareto-optimality-based multi-objective tabu search (MOTS) algorithm to the machine-part grouping problems with multiple objectives: minimizing the weighted sum of inter-cell and intra-cell moves and minimizing the total cell load variation A new approach is developed to evaluate the non-dominance of solutions produced by the tabu search. Comparisons between MOTS and the genetic algorithm (GA) are done and the results show that MOTS is quite promising in multi-objective cell design.
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