标题： 两阶段分布鲁棒优化在交叉码头门设计中的应用 显示英文标题

标题： Two-stage Distributionally Robust Optimization for Cross-dock Door Design

摘要： 交叉装卸门设计问题包括在不确定性条件下决定卸货门和堆叠门的分配以及实体的名义容量。 从起源节点到达的货物流入被分配到卸货门，在实体内进行整合，而出货流则被分配到堆叠门以交付到目的地节点，从而实现最低成本。 该问题结合了三种高度计算上的困难，即NP难组合学、主要参数中的不确定性及其概率分布。 为了处理这些不确定性，考虑了分布鲁棒优化。 针对交叉装卸问题，提出了与此相关的两阶段混合二进制二次模型；第一阶段决策与实体的设计有关；第二阶段决策与商品流向有限情景集中的门分配有关，这些情景集成员属于模糊集。 目标是最小化模糊集中最高的总成本，同时满足每个成员的约束系统以及随机占优风险厌恶函数。 据我们所知，虽然其应用领域非常广泛，但这个具有挑战性的问题以前尚未被解决。 鉴于问题求解的难度，提出了基于场景聚类分解和基于最小-最大值的数学启发式方法，分别用于获得下界和上界。 计算研究验证了这一提议；它优于直接使用最先进的求解器Cplex和Gurobi。 显示英文摘要

摘要： The cross-dock door design problem consists of deciding the strip and stack doors and nominal capacity of an entity under uncertainty. Inbound commodity flow from origin nodes is assigned to the strip doors, it is consolidated in the entity, and the outbound flow is assigned to the stack ones for being delivered to destination nodes, at a minimum cost. The problem combines three highly computational difficulties, namely, NP-hard combinatorics, uncertainty in the main parameters and their probability distribution. Distributionally robust optimization is considered to deal with these uncertainties. Its related two-stage mixed binary quadratic model is presented for cross-dock problem-solving; the first stage decisions are related to the design of the entity; the second stage ones are related to the assignment of the commodity flow to the doors in a finite set of scenarios for the ambiguity set members. The goal is to minimize the highest total cost in the ambiguity set, subject to the constraint system for each of those members and the stochastic dominance risk averse functional. As far as we know, the challenging problem that results has not been addressed before, although its application field is a very broad one. Given the problem-solving difficulty, a scenario cluster decomposition and a min-max based matheuristic are proposed for obtaining lower and upper bounds, respectively. A computational study validates the proposal; it overperformances the straightforward use of the state-of-the-art solvers Cplex and Gurobi.