Soriano Adria, Gansterer Margaretha, Hartl Richard F
Department for Business Administration, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria.
OR Spectr. 2018;40(4):1077-1108. doi: 10.1007/s00291-018-0534-2. Epub 2018 Oct 16.
Logistics networks are constantly evolving such that new and more varied structures arise and need to be studied. Carriers are aiming for opportunities to save costs by efficient planning. Motivated by this, we define the two-region multi-depot pickup and delivery problem. A region in this setting refers to an area where customers and depots are located. We differentiate two kinds of requests depending on whether their customers are located in the same region or not. Due to geographical characteristics, direct transportation between different regions is considered inefficient and a long-distance transportation mode needs to be used to connect them. Hence, we face a complex problem where interrelated decisions are to be made. We propose a decomposition into three subproblems, which relate to well-known problems in the literature. For solving the global problem, an adaptive large neighborhood search (ALNS) algorithm is developed. The algorithm mixes operators tailored to each of the different decisions of each subproblem. We demonstrate that these operators are efficient when applied to problems of their primal nature. In an extensive computational study, we show that the proposed ALNS dominates alternative ALNS schemes, where subproblems are treated sequentially. A detailed analysis of the solution convergence is provided. The proposed approach is a powerful tool to tackle complex decision problems in large distribution networks.
物流网络在不断演变，从而产生了新的、更加多样的结构，需要对其进行研究。运输商致力于通过高效规划来节省成本。受此推动，我们定义了双区域多配送中心取送货问题。在此情境中，一个区域指的是客户和配送中心所在的区域。我们根据客户是否位于同一区域来区分两种请求。由于地理特征，不同区域之间的直接运输被认为效率低下，需要采用长途运输模式来连接它们。因此，我们面临一个需要做出相互关联决策的复杂问题。我们提出将其分解为三个子问题，这三个子问题与文献中已知的问题相关。为了解决全局问题，开发了一种自适应大邻域搜索（ALNS）算法。该算法混合了针对每个子问题的不同决策量身定制的算子。我们证明，当将这些算子应用于其原始性质的问题时是有效的。在广泛的计算研究中，我们表明所提出的ALNS优于子问题按顺序处理的替代ALNS方案。提供了对解收敛性的详细分析。所提出的方法是解决大型配送网络中复杂决策问题的有力工具。
