This research presents a problem relevant to production scheduling for mixed models – production schedules that contain several unique items, but each unique item may have multiple units that require processing. The presented research details a variant of this problem where, over multiple processes, resequencing is permitted to a small degree so as to exploit efficiencies with the intent of optimizing the objectives of required set-ups and parts usage rate via an efficient frontier. The problem is combinatorial in nature. Enumeration is used on a variety of test problems from the literature, and a search heuristic is used to compare optimal solutions with heuristic based solutions. Experimentation shows that the heuristic solutions approach optimality, but with opportunities for improvement.
P. R. McMullen and G. V. Frazier, “A Simulated Annealing Approach to Mixed-Model Sequencing with Multiple Objectives on a Just in Time Line,” IIE Transactions, Vol. 32, No. 8, 2000, pp. 679-686.
A. Joly and Y. Frein, “Heuristics for an Industrial Car Sequencing Problem Considering Paint and Assembly Shope Objectives,” Computers & Industrial Engineering, Vol. 55, No. 2, 2008, pp. 295-310.
P. R. McMullen, “A Kohonen Self-Organizing Map Approach to Addressing a Multiple Objective, Mixed Model JIT Sequencing Problem,” International Journal of Production Economics, Vol. 72, No. 1, 2001, pp. 59-71.
P. R. McMullen, “An Ant Colony Optimization Approach to Addressing a JIT Sequencing Problem with Multiple Objective,” Artificial Intelligence in Engineering, Vol. 15, No. 3, 2001, pp. 309-317.