Inventory reallocation in a fashion retail network: A matheuristic approach
研究了时尚零售网络中从中央仓库到直营店和加盟店的库存再分配问题，提出一种数学启发式方法，通过求解最大权重匹配问题来减少决策变量，并在实际数据上验证了可行性。
We consider a fashion retail network consisting of a central warehouse, owned by a fashion firm, and a fairly large number of retail stores. Some stores are owned by the firm itself, whereas others are owned by franchisees. An initial inventory allocation decision is made at the beginning of the selling season and is periodically revised. Inventory reallocation comprises both direct shipments from the warehouse to stores and lateral shipments among the stores. Besides stock availability and shipping costs, a suitable reallocation policy must take into account the probability of selling each item, some operational constraints, as well as other preference factors that define the utility of shipping an item from a node of the network to another one. Since the problem does not lend itself to the application of typical tools from inventory theory, we propose an optimization model that complements such tools. The model, given the number of nodes and SKUs, may involve about one million binary variables, and just solving the LP relaxation may take hours using state-of-the-art software. Since typical metaheuristics for combinatorial optimization do not seem a viable alternative, we propose a matheuristic approach, in which a sequence of maximum-weight matching problems is solved in order to reduce the problem and restrict the set of potential shipping pairs, with a corresponding drop in the number of decision variables. Computational results obtained on a set of real-life problem instances are discussed, showing the viability of the proposed algorithm.