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The Optimal Pricing and Multi-Item Capacitated Lot Sizing Problem

机译:最优定价和多项目容量批量问题

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The multi-item capacitated lot sizing problems (MCLSP) extensively studied paid little attention to the product prices and neglected the effects of market on production. However, pricing and production are coordinated here, and the dynamic product prices are introduced into our model as the decision variables. The product demand is a function of the product price. An item-by-item heuristic algorithm is developed, which transforms the J-item problem into J single-item problems. The algorithm also includes a Lagrangean upper bound problem and a Lagrangean lower bound problem. A special case with linear demand function of price concludes that although MCLSP is an NP-hard problem, our model seems to be easier to solve from a numerical point of view than MCLSP. The algorithm may improve the firm's profit in comparison with the decentralized policy and the coordination policy with constant price over time.
机译:广泛研究的多项目容量批量问题(MCLSP)很少关注产品价格,而忽略了市场对生产的影响。但是,这里的价格和生产是协调的,动态产品价格作为决策变量引入到我们的模型中。产品需求是产品价格的函数。开发了逐项启发式算法,将J项问题转化为J项问题。该算法还包括拉格朗日上限问题和拉格朗日下限问题。具有价格线性需求函数的特例得出的结论是,尽管MCLSP是一个NP难题,但从数值的角度来看,我们的模型似乎比MCLSP更容易求解。与分散的策略和协调的,价格随时间变化的策略相比,该算法可以提高企业的利润。

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