Price and Assortment Optimization for Reusable Resources
Price and Assortment Optimization for Reusable Resources
复制标题
可重复使用资源的价格和分类优化
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
D. Simchi
中科院分区：
文献类型：
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作者：
Zachary Owen;D. Simchi
当客户到达率随时间变化时，我们开发了可重用资源系统中具有异构客户偏好的价格和分类优化技术。我们的结果适用于有限时间范围和无限时间范围的情况下，客户到达率周期性变化。在仅约束设置，我们开发了一个随机化的政策，实现了恒定的因素保证最优的动态政策。我们提出的算法是计算上可行的，并允许操作员之间的理论保证和计算工作量的权衡。我们将这些结果扩展到联合定价和分类问题，但我们也表明，计算这些政策可以在计算上具有挑战性。尽管如此，我们展示的技术，开发联合定价和分类策略，在实际相关的特殊情况下。我们进一步提出了动态的政策，在对比贪婪的政策有效的帐户随着时间的推移的资源价值。我们基于真实的世界停车位利用率的计算实验，证明了在做出运营决策时考虑此值的重要性。
We develop techniques for price and assortment optimization in systems of reusable resources with heterogeneous customer preferences when customer arrival rates vary over time. Our results are applicable in both the case of a finite-time horizon and an infinite time horizon in which customer arrival rates vary periodically. In the assortment-only setting we develop a randomized policy attaining a constant-factor guarantee with respect to the optimal dynamic policy. Our proposed algorithm is computationally feasible and allows an operator to trade-off between theoretical guarantees and computational effort. We extend these results to the joint pricing and assortment problem however we also demonstrate that computing these policies can be computationally challenging in general. Despite this we demonstrate techniques to develop joint pricing and assortment strategies in practically relevant special cases. We further propose dynamic policies that in contrast to a greedy policy effective account for the value of resources over time. Our computational experiments based on real world parking bay utilization, demonstrate the importance of accounting for this value in making operational decisions.