LAUSR

Abstract In this article, we study the order fulfillment problem, which integrates order allocation and order routing decisions of an online retailer. Our problem is to find the best way to fulfill each customer’s order to minimize the transportation cost. We first present a mixed-integer programming formulation to help online retailers optimally fulfill customers’ order. We then introduce an adaptive large neighborhood search-based approach for this problem. With extensive computational experiments, we demonstrate the effectiveness of the proposed approach, by benchmarking its performance against a leading commercial solver and a greedy heuristic. Our approach can produce high-quality solutions in short computing times. We also experimentally show that products overlap among different fulfillment centers does affect the operation expense of e-tailers.