A New Multi-Objective Firework Algorithm to Solve the Multimodal Planning Network Problem

Mouna Gargouri Mnif and Sadok Bouamama
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Mouna Gargouri Mnif: ENSI, University of Manouba, Manouba, Tunisia
Sadok Bouamama: Higher College of Technology, HCT, DMC, Dubai, UAE

International Journal of Applied Metaheuristic Computing (IJAMC), 2020, vol. 11, issue 4, 91-113

Abstract: This article introduces a new approach called multi-objective firework algorithm (MFWA). The proposed approach allows for solving the multimodal transportation network problem (MTNP). The main goal is to develop a decision system that optimizes and determines the planning network of the multimodal transportation (PNMT) problem. The optimization involves reaching the efficient transport mode and multimodal path, in order to move from one country to another while satisfying the set of objectives. Moreover, the firework algorithm has distinct advantages in solving complex optimization problems and in obtaining a solution by a distributed and oriented research system. This approach presents a search way, which is different from the swarm intelligence-based stochastic search technique. For each firework, the process starts by exploding a firework in the sky. The search space is filled with a shower of sparks to get diversity solutions. This new approach proves their efficacy in solving the multi-objective problem, which is shown by the experimental results.

Date: 2020
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