ABSTRACT

In this paper, the effect of load bundling on overall costs, service level, and CO₂ emissions is evaluated for a multi-stage, multi-item supply chain. A simulation-based optimisation approach is used to optimize the inventory management parameters reorder point and lot size. The optimisation approach consists of a simulation model and a metaheuristic search procedure, which is a subclass of the evolutionary algorithm. For the evaluation of the load bundling opportunity in different demand structures, a multicriterial objective function is optimized. The paper shows that the load bundling opportunity has significant cost and environmental benefits. The study points out that the load bundling opportunity leads to smaller and more customer-driven lot sizes which simultaneously reduce the carbon emissions. Finally, results show that for medium to high service level target values, ABC-clustered order rate scenarios lead to lower supply chain costs than demand scenarios with an identical order rate for all items.

摘要

在本文中，负载捆绑对总成本、服务水平和 CO _2的影响对多阶段、多项目供应链的排放进行评估。基于模拟的优化方法用于优化库存管理参数再订货点和批量。优化方法由模拟模型和元启发式搜索程序组成，它是进化算法的子类。为了评估不同需求结构中的负载捆绑机会，优化了多准则目标函数。该论文表明，负载捆绑的机会具有显着的成本和环境效益。该研究指出，负载捆绑机会导致更小和更多由客户驱动的批量，同时减少碳排放。最后，结果表明，对于中到高服务水平的目标值，