首页> 外文会议>International Conference on Computers Industrial Engineering >A NEW APPROACH TO THE PROBLEM OF MULTI-OBJECTIVE OPTIMIZATION FOR THE GREEN VEHICLE ROUTING PROBLEM: A CASE STUDY OF THE NEWSPAPER DISTRIBUTION PROBLEM
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A NEW APPROACH TO THE PROBLEM OF MULTI-OBJECTIVE OPTIMIZATION FOR THE GREEN VEHICLE ROUTING PROBLEM: A CASE STUDY OF THE NEWSPAPER DISTRIBUTION PROBLEM

机译:绿色汽车路径问题多目标优化问题的一种新方法 - 以报纸分布问题为例

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Logistic distribution results in many costs for organizations and, therefore, opportunities for optimization in this field are always welcome. The aim of this work is to present a solution procedure referred to here as the Multi-objective Optimization for Green Vehicle Routing Problem (MOOGVRP) to provide solutions for a case study. The proposed methodology consists of three stages to resolve Scenario A. Stage 1 consists of the "treatment" of data; Stage 2 consists of applying mathematical models of the p-Median Capacitated Problem (with the objectives of minimization of distances and homogenization of demands between groups) and the Asymmetric Traveling Salesman Problem (with the objectives of minimizing distances and minimizing time). The weighted method was used as the multi-objective procedure. In Stage 3, an analysis of the results is conducted, taking into consideration the environmental aspects related to the case study, more specifically with regard to fuel consumption and air pollutant emission. This methodology was applied to a (partial) database that addresses newspaper distribution in the municipality of Curitiba, Parana State, Brazil. The preliminary findings for Scenario A showed that it was possible to improve the distribution of the load, reduce the mileage and the greenhouse gas by 17.32% and the journey time by 22.58% in comparison with the current scenario. The intention for future works is to use other multi-objective techniques and an expanded version of the database and explore the triple bottom line of sustainability.
机译:物流分布导致组织的许多成本,因此,始终欢迎在该领域优化的机会。这项工作的目的是提出一个解决方案程序,称为绿色车辆路由问题(MOOGVRP)的多目标优化,以提供案例研究的解决方案。提出的方法包括三个阶段来解决方案A.阶段1由数据的“治疗”组成;第2阶段包括应用P-中值电容问题的数学模型(以最小化距离和组之间的距离和均匀化的目标)和非对称的旅行推销员问题(具有最小化距离和最小化时间的目标)。加权方法用作多目标程序。在第3阶段,考虑到案例研究相关的环境方面,对结果进行了分析,更具体地说,关于燃料消耗和空气污染物排放。该方法适用于解决库里提巴(Parana State)的报纸分布的(部分)数据库中,以巴西Parana State。情景A的初步调查结果表明,与当前情景相比,可以提高载荷的分布,将里程和温室气体降低17.32%,行程时间为22.58%。未来作品的意图是使用其他多目标技术和数据库的扩展版本,并探索可持续性的三倍底线。

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