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A Comparison of Different Solution Approaches to Simultaneous Manufacturing Kanban Design and Scheduling
Abstract
This paper evaluates several artificial intelligence heuristics for the simultaneous Kanban system design and scheduling on flexible manufacturing systems. The objective of the problem is to minimize the total production cost that includes due date penalty, inventory, and machining costs. We show that the simultaneous Kanban design and scheduling decisions are critical in minimizing the total production cost (approximately 40% cost reduction over scheduling without Kanban design decision). To identify the most effective search method for the simultaneous Kanban design and scheduling, we evaluated widely known artificial intelligence heuristics: genetic algorithm, simulated annealing, tabu search, and neighborhood search. Computational results show that the tabu search performs best in terms of solution quality. The tabu search also requires much less computational time than the genetic algorithm and simulated annealing.
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