Electric Vehicle Fleet Management Using Ant Colony Optimisation

Muriel, Javier Biera; Fotouhi, Abbas

doi:10.4018/ijose.2020010101

Cited by 4 publications

(1 citation statement)

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“…A data clustering technique to divide a dataset into a few unsupervised data analysis partitions based on GEM was presented in [22]. The ACO was used in [42] to solve an advanced version of the vehicle routing problem called the fleet management system. In [28] PSO was used to improve the quality of the video for giving effective results in the video analysis process.…”

Section: Introductionmentioning

confidence: 99%

Multi-level parallel chaotic Jaya optimization algorithms for solving constrained engineering design problems

et al. 2021

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Several heuristic optimization algorithms have been applied to solve engineering problems. Most of these algorithms are based on populations that evolve according to different rules and parameters to reach the optimal value of a function cost through an iterative process. Different parallel strategies have been proposed to accelerate these algorithms. In this work, we combined coarse-grained strategies, based on multi-populations, with fine-grained strategies, based on a diffusion grid, to efficiently use a large number of processes, thus drastically decreasing the computing time. The Chaotic Jaya optimization algorithm has been considered in this work due to its good optimization and computational behaviors in solving both the constrained optimization engineering problems (seven problems) and the unconstrained benchmark functions (a set of 18 functions). The experimental results show that the proposed parallel algorithms outperform the state-of-the-art algorithms in terms of

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Section: Introductionmentioning

confidence: 99%