Sequencing mixed-model assembly lines with demand management: problem development and efficient multi-objective algorithms

Abstract

As a kind of production line, the mixed-model assembly line (MMAL) has been progressively adopted by industries to satisfy the diversification of customer demands. This study applied an MMAL sequencing problem for a make-to-order (MTO) strategy. Using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach, this study sorted customer orders, satisfying these by a desired due date being the main feature in MTO systems. This MMAL problem was investigated to achieve three minimization objectives: total set-up cost, number of work overload situations, and total earliness and tardiness costs, according to the specified priority of orders. Accordingly, a multi-objective particle swarm optimization (MOPSO) algorithm was developed for the proposed NP-hard model and the algorithm parameters were tuned by applying the Taguchi technique to the experimental design. The computational results of a comparison between the proposed MOPSO model and four multi-objective algorithms confirmed its advantages.