Optimal and heuristic policies for lot sizing with learning in setups
研究了当设置成本因持续改进、学习效应和流程变化而随时间降低时，如何确定最优和启发式的批量规模，帮助管理者评估设备或培训投资。
Abstract We develop heuristic and optimal methods for determining lot sizes when setup cost reductions occur over time due to emphasis on continuous improvement, learning effects and incremental process changes. Our heuristic methods are intuitively appealing, easy to implement, require little information about setup costs, and have low computational burden. Computational studies show that choosing the appropriate heuristic yields nearly optimal solutions. Recommendations for choosing the appropriate heuristic are also provided. The optimal method developed in this paper is also useful to managers for evaluating investments in hardware and/or worker training for setup reduction. Concepts and methods are illustrated with numerical examples. Managerial implications of using our policies are discussed.