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For automated manufacturing systems (AMSs), deadlock resolution in terms of Petri nets remains an attractive topic to which many approaches are dedicated. However, few of them can quantitatively optimize certain indices during their supervisor synthesis process. This causes unnecessary control limitations and often leads to high implementation cost. In the framework of Petri nets, this paper proposes a method to synthesize a cost-effective supervisor with the aid of a set of mathematical programming formulations. Along the same vein, we also show some results by investigating timed Petri nets, which can be utilized to make a good tradeoff between implementation cost and system cycle time. Examples are used to validate the effectiveness of our result.