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Optimal pricing for build-to-order supply chain design under price-dependent stochastic demand

机译:基于价格的随机需求下按订单生产的供应链设计的最优定价

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Build to order (BTO) is a supply chain disruption mitigation strategy. Whereas cost minimization is an operational objective, the goal of the BTO manufacturer is to maximize its profit by using pricing as its competitive decision-making strategy. In this paper, we study a BTO manufacturer who simultaneously determines its product prices and designs its supply chain network to maximize its expected profit under price-dependent stochastic demand. We propose an L-shaped decomposition with complete enumeration to solve for optimality and show that the expanded master problem remains convex programming, although the optimality cuts are quadratic inequalities. The computational results demonstrate that stocking up on differentiated components and allocating modules appropriately to meet realized demand is a resilient policy that sustains variations in demand. Furthermore, the pricing decision balances the expected revenue and expected operating cost with an increase in expected profit. The integration of pricing and operational planning results in a higher expected profit than by individual decisions. We also demonstrate that cost minimization may not provide the same level of profit if the manufacturer overestimates or underestimates its most profitable demand.
机译:按订单制造(BTO)是缓解供应链中断的策略。最小化成本是一个运营目标,而BTO制造商的目标是通过使用定价作为其竞争性决策策略来最大化其利润。在本文中,我们研究了一家BTO制造商,该制造商同时确定其产品价格并设计其供应链网络,以在价格依赖的随机需求下最大化其预期利润。我们提出了一个具有完整枚举的L形分解来求解最优性,并表明尽管最优性割是二次不等式,但扩展后的主问题仍然是凸规划。计算结果表明,在差异化组件上进行库存并适当分配模块以满足已实现的需求,这是一种能够维持需求变化的弹性策略。此外,定价决策平衡了预期收入和预期运营成本与预期利润的增长。定价和运营计划的集成比单个决策产生的预期利润更高。我们还证明,如果制造商高估或低估其最有利可图的需求,那么最小化成本可能无法提供相同水平的利润。

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