Completion of FCVRP using Hybrid Particle Swarm Optimization Algorithm

Abstract

The issue of green logistics has received full attention from the government and business people. It is closely related to the increase in Green House Gas (GHG) by transportation activities in the logistics sector. Controlling fuel consumption in transportation activities is fundamental in dealing with GHG. Therefore, the Fuel Consumption Vehicle Routing Problem (FCVRP) is proposed as a solution model in optimizing fuel consumption in the logistics sector. This study aims to develop a Hybrid Particle Swarm Optimization (HPSO) algorithm to solve the FCVRP problem. The proposed algorithm is the development of the PSO algorithm with local procedures search. Several experiments were carried out to determine the HPSO parameter's effect on the minimization of fuel consumption at issue in the FCVRP. The results of the experiment show that HPSO is effective for optimizing fuel consumption in the FCVRP study.

A novel hybrid jellyfish algorithm for minimizing fuel consumption capacitated vehicle routing problem

“…In addition, population parameters and large iterations can result in the lowest possible fuel consumption costs. The results of the comparison of the proposed algorithm against the HPSO [20], Hybrid TS [21], and ELS [22] algorithms are presented in Table 2. In the case of 10 nodes, the proposed algorithm produces the same solution as the comparison algorithm.…”

“…Several FCCVRP studies have emphasized the importance of taking load into account when calculating fuel consumption. Ali and Farida [20] used the hybrid PSO (HPSO) algorithm, which resulted in increased fuel consumption due to increased load. Niu et al [21] investigated this factor using novel hybrid tabu search (hybrid TS).…”

“…In addition, the proposed algorithm was compared to the previous algorithm in this study. Some of the comparison algorithms used were HPSO [20], Hybrid TS [21], dan ELS [22]. Algorithm comparisons were performed on 10, 20, 50, 60, 90, and 100 nodes.…”

A Novel Hybrid Spotted Hyena Optimizer: An Algorithm for Fuel Consumption Capacitated Vehicle Routing Problem

“…This indicated the utilization of three variations, namely small (15 and 25 customers), medium (50 and 60 customers), and large (90 and 100 customers) cases, respectively. The utilized comparison algorithm was also SA (Kuo 2010), ACO (Yao et al, 2015), GA (Xiong, 2010), HPSO (Ali and Farida, 2021), Teaching-Learning-Based Optimization (TLBO) (Trachanatzi et al, 2021). These algorithms were then operated with 200 iterations and 500 population through the Matlab 2014a software on Windows 10 AMD A12 x64-64 8GB RAM processor.…”

“…This indicated that the distance to estimate fuel consumption was generally considered, although it was still affected by the vehicle load between the nodes. In calculating fuel consumption, loads have recently been considered in several FCCVRP studies, indicating the development of metaheuristic algorithms such as SA (Xiao et al, 2012), as well as Novel Hybrid TS (Niu et al, 2018) and Hybrid PSO (Ali and Farida, 2021). These aligned with Zhang, Wei, and Lim (2015), where a local evolutionary search was provided for the problem.…”