This paper studies an open question in the warehouse problem where a merchant trading a commodity tries to find an optimal inventory-trading policy to decide on purchase and sale quantities during a fixed time horizon in order to maximize their total pay-off, making use of fluctuations in sale and cost prices. We provide the first known polynomial-time algorithms for the case when there are fixed costs for purchases and sales, optional complementarity constraints that prohibit purchasing and selling during the same time period, and bounds on purchase and sales quantities. We do so by providing an exact characterization of the extreme points of the feasible region and using this to construct a suitable network where a min-cost flow computation provides an optimal solution. We are also able to provide polynomial extended linear formulations for the original feasible regions. Our methods build on the work by Wolsey and Yaman (Discrete Optimization 2018). We also consider the problem without fixed costs and provide a fully polynomial time approximation scheme in a setting with time-dependent bounds.
翻译:本文研究仓库问题中的一个未决问题,即商品交易商试图找到最佳的存货交易政策,在固定时间范围内决定购买和销售数量,以便利用销售和成本价格的波动,最大限度地实现总回报率,利用销售和成本价格的波动;我们为有固定的购买和销售成本的情况提供第一种已知的多元时间算法,禁止在同一时间段进行买卖的选择性互补限制,以及对购买和销售量的限制;我们这样做的方式是对可行区域的极端点作出精确的描述,并利用它建立一个适当的网络,在该网络中,以低成本流量计算提供最佳的解决办法;我们还能够为最初可行的区域提供多元扩展线性线性配方;我们的方法以Wolsey和Yaman的工作为基础(2018年Discrete Opptimization),我们还考虑没有固定费用的问题,并在有时限的情况下提供一个完全多数值的时间近似计划。