A joint production-workforce-delivery stochastic planning problem for perishable items
针对易腐品供应链，提出一个同时整合库存、生产、配送、路径和劳动力规划的随机模型，并设计高效混合算法求解，帮助管理者理解联合决策的价值。
Despite the existence of a rich literature on Production Routing Problem (PRP), the lack of investigations on the workforce planning, and its impact on costs and productivity of the organisation caught our attention. This paper aims to fill this gap by designing a novel framework to integrate inventory, production, distribution, routing, and workforce planning decisions simultaneously. Because of the potential long distances between the main plant and the retailers spread throughout the country and also the perishability nature of the products, considering travelling time uncertainty for delivering products is necessary to have feasible decisions. The application of the proposed approach is investigated by being inspired from a supply chain structure from a knowledge-based company. We derive managerial insights on the benefit of an integrated decision. Besides, given the size and complexity of the proposed problem, we were challenged by exactly solving it in a reasonable time. We succeeded to reach this target by designing an innovative hybrid algorithm. Computational experiments on several numerical examples applied on both the studied real case and on PRP literature instances reveal the effectiveness and efficiency of our new hybrid method and permits to derive interesting managerial insights on the joint decisions.