Development of Ant Colony Optimization Algorithm for Green Capacitated Vehicle Routing Problem

被引：3

作者：

Adhitama, Lukman ^{[1
]}

Kurniawati, Dwi Agustina ^{[1
]}

机构：

[1] Univ Islam Negeri Sunan Kalijaga Yogyakarta, Fac Sci & Engn, Ind Engn Dept, Optimizat Operat Res & Ind Syst Res Grp 2ORIS RG, Jl Marsda Adisucipto, Yogyakarta, Indonesia

来源：

JOURNAL OF ADVANCED MANUFACTURING SYSTEMS | 2023年 / 22卷 / 02期

关键词：

Emission; Green capacitated vehicle routing problem; Ant colony optimization; Variable neighborhood search; VARIABLE NEIGHBORHOOD SEARCH; SUPPLY CHAIN; DEPOT; MODEL; DELIVERY; DESIGN;

D O I：

10.1142/S0219686723500154

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The high customer demand for a product will lead to increased distribution activity by the vehicles, causing an increase in the amount of gas emissions that pollute the air. Therefore, the common problem namely the Capacitated Vehicle Routing Problem should also seek a reduction of emissions that is known as the Green Capacitated Vehicle Routing Problem (GCVRP). This research was conducted in three steps. First, all nodes are divided into clusters. After that, the Ant Colony Optimization (ACO) algorithm is used to determine the route of each cluster so as to provide minimal emissions. In the final step, the results are corrected by using the Variable Neighborhood Search. Results of this research indicate a reduction of 38.53% of emission value.

引用

页码：307 / 322

页数：16

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