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Integrated low-carbon location-routing method for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

机译:用于产品分销供应链需求侧的集成式低碳选址路由方法:基于能源部的MOPSO优化器解决方案

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摘要

This article contributes to location-routing literature on three inter-linked aspects viz., formulation of a novel integrated low-carbon/green location-routing model for the demand side of a Supply Chain (SC) with a single product and multiple consumers, i.e., Drop-off Points (DoPs), a novel and robust solution approach through a Design of Experiment (DoE)-guided Multiple-Objective Particle Swarm Optimisation (MOPSO) optimiser and exhaustive analysis of the location-routing solutions (i.e., prioritisation, ranking and scenario analysis). The total costs, CO2 emission and the traversed distances of the vehicles during transportation are optimised. The optimisation model for the strategic decision-making is formulated by effectively integrating the 0-1 mixed-integer programming with a green constraint based on Analytic Hierarchy Process (AHP). Due to the computationally NP-hard characteristic of the model a systematic and technically robust DoE-guided solution approach is designed using a commercial solver – modeFRONTIER® . DoE guides the solution through the MOPSO optimiser in order to eliminate the un-realistic set of feasible and optimal solution sets. A popular multi-attribute decision-making approach, TOPSIS, evaluates the solutions found from the Pareto optimal solution space of the solver. Finally decision-makers’ preferences are analysed for monitoring the changes in the controlling parameters with respect to the changes in the decisions. A scenario analysis of the location-routing events by considering alternative possible outcomes is also conducted. It is found that the implemented methodology successfully routes the vehicles with optimal costs and low-carbon emission thus contributing to greening the environment on the demand side of a SC network.
机译:本文为有关三个相互联系的方面的位置路由文献做出了贡献,即为具有单个产品和多个消费者的供应链(SC)的需求方制定了新颖的低碳/绿色集成位置路由模型,即落点(DoPs),这是一种通过实验设计(DoE)指导的多目标粒子群优化(MOPSO)优化器对位置路由解决方案进行详尽且详尽的分析(即优先排序,排名和情景分析)。优化了运输过程中的总成本,二氧化碳排放量和车辆的行驶距离。通过将基于层次分析法(AHP)的0-1混合整数规划与绿色约束有效地集成,制定了战略决策优化模型。由于该模型具有计算上的NP-hard特性,因此使用商用求解器–modeFRONTIER®设计了一种系统且技术上可靠的DoE指导的解决方案。美国能源部通过MOPSO优化器指导解决方案,以消除不切实际的可行和最佳解决方案集。流行的多属性决策方法TOPSIS评估从求解器的帕累托最优解空间中找到的解。最后,分析决策者的偏好,以监控与决策变化有关的控制参数的变化。还通过考虑其他可能的结果对位置路由事件进行了情景分析。结果发现,实施的方法成功地以最佳成本和低碳排放为车辆提供了路线,从而有助于在SC网络的需求侧实现绿色环保。

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