An efficient frontier approach to addressing JIT sequencing problems with setups via search heuristics

This research presents a technique to obtain production sequences where sch eduling flexibility and number of setups are considered. These two objectiv es of flexibility and setups are typically inversely correlated with each o ther, so simultaneous optimization of both is challenging. Another challeng ing issue is the combinatorial nature of such sequencing problems. An effic ient frontier approach is exploited where simultaneous maximization of flex ibility and minimization of setups is desired. The efficient frontier is co nstructed via the popular search heuristics of Genetic Algorithms, Simulate d Annealing and Tabu Search. For several test problems from the literature, it is discovered that the efficient frontiers obtained via the three searc h heuristics provide near optimal results for smaller problems, and for lar ger problems, the Simulated Annealing and Tabu Search approaches outperform the Genetic Algorithm approach. (C) 2001 Elsevier Science Ltd. An rights r eserved.