Memetic chicken swarm algorithm for job shop scheduling problem

Author:

Semlali Soukaina cherif bourki,Riffi Mohammed Essaid,Chebihi Fayçal

Abstract

<p>This paper presents a Memetic Chicken swarm optimization (MeCSO) to solve job shop scheduling problem (JSSP). The aim is to find a better solution which minimizes the maximum of the completion time also called Makespan. In this paper, we adapt the chicken swarm algorithm which take into consideration the hierarchical order of chicken swarm while seeking for food. Moreover, we integrate 2-opt method to improve the movement of the rooster. The new algorithm is applied on some instances of ORLibrary. The empirical results show the forcefulness of MeCSO comparing to other metaheuristics from literature in term of run time and quality of solution.</p>

Publisher

Institute of Advanced Engineering and Science

Subject

Electrical and Electronic Engineering,General Computer Science

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Learning-Based Grey Wolf Optimizer for Job Shop Scheduling Problem;2023 16th International Conference on Developments in eSystems Engineering (DeSE);2023-12-18

2. Multi-objective FJSP Based on Multi-agent Reinforcement Learning Algorithm;2023 6th International Conference on Computer Network, Electronic and Automation (ICCNEA);2023-09-22

3. VGATS-JSSP: Variant Genetic Algorithm and Tabu Search Applied to the Job Shop Scheduling Problem;Hybrid Intelligent Systems;2023

4. A New Frequency Analysis Operator for Population Improvement in Genetic Algorithms to Solve the Job Shop Scheduling Problem;Sensors;2022-06-17

5. Extremely Fast Heuristic Event-Driven Job Shop Scheduler With a New Class of Extended Petri Nets;Advances in Marketing, Customer Relationship Management, and E-Services;2021

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