Improved Bacteria Foraging Optimization Algorithm for Solving Flexible Job-Shop Scheduling Problem

Xingang Wang, Pengfei Yi

Abstract

Bacterial foraging algorithm (BFO) is an emerging algorithm, which has been widely applied in many fields by researchers . This paper designed an improved adaptive step and stop condition for solving localoptimal and premature problems, and applied this improved algorithm to the flexible job-shop scheduling Problem(FJSP). According to the changes of crowding lever between bacteria, step’s evaluation are divided into three stages. Numerical simulation shows that the improved algorithm has avoided local optimal and premature problems,and is superior to standard BFOA and genetic algorithm.

References

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Paper Citation


in Harvard Style

Wang X. and Yi P. (2016). Improved Bacteria Foraging Optimization Algorithm for Solving Flexible Job-Shop Scheduling Problem . In ISME 2016 - Information Science and Management Engineering IV - Volume 1: ISME, ISBN 978-989-758-208-0, pages 63-67. DOI: 10.5220/0006443800630067


in Bibtex Style

@conference{isme16,
author={Xingang Wang and Pengfei Yi},
title={Improved Bacteria Foraging Optimization Algorithm for Solving Flexible Job-Shop Scheduling Problem},
booktitle={ISME 2016 - Information Science and Management Engineering IV - Volume 1: ISME,},
year={2016},
pages={63-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006443800630067},
isbn={978-989-758-208-0},
}


in EndNote Style

TY - CONF
JO - ISME 2016 - Information Science and Management Engineering IV - Volume 1: ISME,
TI - Improved Bacteria Foraging Optimization Algorithm for Solving Flexible Job-Shop Scheduling Problem
SN - 978-989-758-208-0
AU - Wang X.
AU - Yi P.
PY - 2016
SP - 63
EP - 67
DO - 10.5220/0006443800630067