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An integrated product planning model for pricing and bundle selection using Markov decision processes and data envelope analysis

机译:使用马尔可夫决策过程和数据包络分析的用于定价和捆绑选择的集成产品计划模型

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摘要

When bundling products during the product planning stage, there are a number of possible combinations that can be offered to customers. Consider a firm that offers N distinctive products, then there are 2~N-(N+1) possible bundling combinations. Now, if we wish to make pricing and bundle selection decisions, keeping in my mind limited inventory and a finite time horizon, then the size of the state space could be very large and finding an optimal solution could be impossible. To tackle this issue, we formulate an integrated model that utilizes a Markov decision process and data envelope analysis. Bundle selections are made using data envelope analysis in each decision epoch. Once the efficient bundles are selected they are priced by solving a Markov decision process using dynamic programming. Numerical examples are solved to exhibit the model's potential in solving real-world problems.
机译:在产品计划阶段捆绑产品时,可以提供多种可能的组合给客户。考虑一家提供N种独特产品的公司,那么有2〜N-(N + 1)种可能的捆绑组合。现在,如果我们希望做出定价和捆绑包选择的决定,并记住有限的库存和有限的时间范围,那么状态空间的规模可能会很大,因此不可能找到最佳解决方案。为了解决这个问题,我们制定了一个综合模型,该模型利用了马尔可夫决策过程和数据包络分析。在每个决策时期使用数据包络分析进行捆绑选择。一旦选择了有效的捆绑包,就可以通过使用动态编程解决马尔可夫决策过程来对其定价。通过数值算例可以展示该模型在解决实际问题中的潜力。

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