Fire and manoeuvrer optimizer for flow shop scheduling problems

作     者：Belabid, Jabrane 

作者机构：Univ Hassan II Casablanca Lab Math & Applicat FST POB 146 Mohammadia Morocco 

出 版 物：《EVOLUTIONARY INTELLIGENCE》 (进化智能)

年 卷 期：2024年第17卷第2期

页      面：977-991页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：UK Research and Innovation  UKRI  (105088) 

主　　题：Hunting algorithm Flow shop Mixed-integer linear programming Nature inspired algorithm 

摘      要：The purpose of this paper is to introduce a new rich source of ideas and techniques that could be used to build new algorithms capable to solve numerous encountered optimisation problems in different fields of science and engineering. The art of war is one of the most rich disciplines in terms of already experimented strategies and tactics that can inspire researchers to design new powerful and efficient metaheuristics. The framework of the proposed method are inspired by the main war phases and contains seven components: initialization, intelligence, conception, suppression, advance, assault and exploitation. The basic fire and manoeuvre tactic is adopted in the suppression and advance phases. The proposed fire and manoeuvre algorithm (FMA) is a hybridization of a greedy algorithm with a multi-neighbouring search procedure. The developed algorithm has been employed to minimize makespan of the classical flow shop scheduling problem. A mathematical model is presented to describe the studied optimisation problem. Comparative experiments on Taillard s data set confirmed that the (FMA) results are more accurate than already published data. A comparison between the FMA and other popular nature-inspired algorithms has been conducted. It was revealed that the proposed metaheuristic outperforms the classical genetic algorithm, the migrating birds optimisation and the whale optimisation algorithm.