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

This research presents a technique to obtain production sequences where scheduling flexibility and number of setups are considered. These two objectives of flexibility and setups are typically inversely correlated with each other, so simultaneous optimization of both is challenging. Another challenging issue is the combinatorial nature of such sequencing problems. An efficient frontier approach is exploited where simultaneous maximization of flexibility and minimization of setups is desired. The efficient frontier is constructed via the popular search heuristics of Genetic Algorithms, Simulated Annealing and Tabu Search. For several test problems from the literature, it is discovered that the efficient frontiers obtained via the three search heuristics provide near optimal results for smaller problems, and for larger problems, the Simulated Annealing and Tabu Search approaches outperform the Genetic Algorithm approach.