区间不确定下多产品的鲁棒价格Optimization
Robust Price Optimization of Multiple Products under Interval Uncertainties
摘要：
本文研究了需求函数中价格敏感性参数为区间不确定的多产品价格最优化问题。价格最优化问题的目标是使企业的总收益最大化，其中决策变量是企业提供的产品的价格。我们提出了一种方法，产生最优解下的不同变化的估计价格敏感性参数。我们采用了一种鲁棒优化方法，通过建立一个数据驱动的不确定性集的参数，然后构建一个确定性的鲁棒最优化模型。数值结果表明，该方法实现了两个目标：一是反映了参数估计中的不确定性，二是得到了最优价格区间。我们还进行了模拟研究，我们比较了我们的方法的结果。比较结果表明，虽然鲁棒优化被认为是保守的，所提出的方法的结果相比，从模拟显示出很小的损失。
英文摘要：
In this paper, we solve the multiple product price optimization problem under interval uncertainties of the price sensitivity parameters in the demand function. The objective of the price optimization problem is to maximize the overall revenue of the firm where the decision variables are the prices of the products supplied by the firm. We propose an approach that yields optimal solutions under different variations of the estimated price sensitivity parameters. We adopt a robust optimization approach by building a data-driven uncertainty set for the parameters, and then construct a deterministic counterpart for the robust optimization model. The numerical results show that two objectives are fulfilled: the method reflects the uncertainty embedded in parameter estimations, and also an interval is obtained for optimal prices. We also conducted a simulation study to which we compared the results of our approach. The comparisons show that although robust optimization is deemed to be conservative, the results of the proposed approach show little loss compared to those from the simulation.
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