A New Hybrid Butterfly Optimization Algorithm for Green Vehicle Routing Problem

被引:26
作者
Utama, Dana Marsetiya [1 ]
Widodo, Dian Setiya [2 ]
Ibrahim, Muhammad Faisal [3 ]
Dewi, Shanty Kusuma [1 ]
机构
[1] Univ Muhammadiyah Malang, Jl Tlogomas 246, Malang 65144, East Java, Indonesia
[2] Univ 17 Agustus 1945 Surabaya, Jl Semolowaru, Surabaya 60118, East Java, Indonesia
[3] Univ Int Semen Indonesia, Jl Vet, Gresik 61122, East Java, Indonesia
关键词
PARTICLE SWARM OPTIMIZATION; COLD CHAIN LOGISTICS; HETEROGENEOUS FLEET; TIME WINDOWS; EMISSIONS; LINEHAUL; DELIVERY;
D O I
10.1155/2020/8834502
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In the industrial sector, transportation plays an essential role in distribution. This activity impacts climate change and global warming. One of the critical problems in distribution is the green vehicle routing problem (G-VRP). This study focuses on G-VRP for a single distribution center. The objective function is to minimize the distribution costs by considering fuel costs, carbon costs, and vehicle use costs. This research aims to develop the hybrid butterfly optimization algorithm (HBOA) to minimize the distribution costs on G-VRP. It was inspired by the butterfly optimization algorithm (BOA), which was by combining the tabu search (TS) algorithm and local search swap and flip strategies. BOA is a new metaheuristic algorithm that has been successfully applied in various engineering fields. Experiments were carried out to test the parameters of the proposed algorithm and vary the speed of vehicles. The proposed algorithm was also compared with several procedures of prior study. The experimental results proved that the HBOA could minimize the total distribution cost compared to other algorithms. Moreover, the computation time is also included in the analysis.
引用
收藏
页数:14
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