Determination of green vehicle routing problem via differential evolution

Kunnapapdeelert, Siwaporn; Klinsrisuk, Ratchaphong

doi:10.1504/ijlsm.2019.10024402

Cited by 1 publication

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“…Some popular algorithms for this problem are GA [34,35], tabu search (TS) [36][37][38], the Clarke and Wright algorithm [39], and GA with dynamic programming [40]. e differential evolution algorithm was developed by Kunnapapdeelert and Klinsrisuk [41] to solve G-VRP with pickup and delivery problems. Molina et al [42] proposed the TS with neighborhood variables to reduce pollutant emissions.…”

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A New Hybrid Butterfly Optimization Algorithm for Green Vehicle Routing Problem

Utama

Widodo

Ibrahim

et al. 2020

Journal of Advanced Transportation

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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.

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