A self‐learning artificial bee colony algorithm based on reinforcement learning for a flexible job‐shop scheduling problem

Author:

Long Xiaojun1ORCID,Zhang Jingtao1,Qi Xing1,Xu Wenlong1,Jin Tianguo2,Zhou Kai1ORCID

Affiliation:

1. College of Mechanical and Electronic Engineering Shandong Agricultural University Tai'an China

2. School of Mechatronics Engineering Harbin Institute of Technology Harbin China

Funder

Agriculture Research System of China

China Postdoctoral Science Foundation

National Defense Basic Scientific Research Program of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference53 articles.

1. Hybrid bee colony algorithm for flexible job shop scheduling problem;Li XL;Comput Integr Manuf Syst,2011

2. Flexible job-shop scheduling with routing flexibility and separable setup times using ant colony optimisation method

3. Maximizing availability for task scheduling in on-demand computing-based transaction processing system using ant colony optimization

4. A self‐learning genetic algorithm based on reinforcement learning for flexible job‐shop scheduling problem;Chen RH;Comput Ind Eng,2020

5. Local Search Genetic Algorithms for the Job Shop Scheduling Problem

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