Reallocation scheduling is one of the most fundamental problems in various areas such as supply chain management, logistics, and transportation science. In this paper, we introduce the reallocation problem that models the scheduling in which products are with fixed cost, non-fungible, and reallocated in parallel, and comprehensively study the complexity of the problem under various settings of the transition time, product size, and capacities. We show that the problem can be solved in polynomial time for a fundamental setting where the product size and transition time are both uniform. We also show that the feasibility of the problem is NP-complete even for little more general settings, which implies that no polynomial-time algorithm constructs a feasible schedule of the problem unless P$=$NP. We then consider the relaxation of the problem, which we call the capacity augmentation, and derive a reallocation schedule feasible with the augmentation such that the completion time is at most the optimal of the original problem. When the warehouse capacity is sufficiently large, we design constant-factor approximation algorithms under all the settings. We also show the relationship between the reallocation problem and the bin packing problem when the warehouse and carry-in capacities are sufficiently large.
翻译:重新定位时间安排是供应链管理、物流和运输科学等不同领域最根本的问题之一。在本文中,我们引入了再分配问题,即模拟以固定成本、不可调换和平行重新分配的产品列表,全面研究在过渡时间、产品规模和能力等不同情况下问题的复杂性。我们表明,对于产品规模和过渡时间都一致的基本环境来说,这个问题可以在多元时间内解决。我们还表明,问题的可行性是NP完成的,即使是在更一般的环境下也是如此,这意味着除非P=NP,否则任何多元时间算法都无法构建出一个可行的问题时间表。我们然后考虑这一问题的缓解,我们称之为能力增强,并得出一个再分配时间表,这样,完成时间最多是最初问题的最佳时机。当仓库容量足够大时,我们在所有环境下设计了常量的近似算法。我们还展示了重新配置问题与仓储和搬运能力足够大时的包装问题之间的关系。