An Improved Genetic-Simulated Annealing Algorithm Based on a Hormone Modulation Mechanism for a Flexible Flow-Shop Scheduling Problem
Joint Authors
Zheng, Kun
Cai, Qixiang
Dai, Min
Tang, Dunbing
Source
Advances in Mechanical Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-19
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
A flexible flow-shop scheduling (FFS) with nonidentical parallel machines for minimizing the maximum completion time or makespan is a well-known combinational problem.
Since the problem is known to be strongly NP-hard, optimization can either be the subject of optimization approaches or be implemented for some approximated cases.
In this paper, an improved genetic-simulated annealing algorithm (IGAA), which combines genetic algorithm (GA) based on an encoding matrix with simulated annealing algorithm (SAA) based on a hormone modulation mechanism, is proposed to achieve the optimal or near-optimal solution.
The novel hybrid algorithm tries to overcome the local optimum and further to explore the solution space.
To evaluate the performance of IGAA, computational experiments are conducted and compared with results generated by different algorithms.
Experimental results clearly demonstrate that the improved metaheuristic algorithm performs considerably well in terms of solution quality, and it outperforms several other algorithms.
American Psychological Association (APA)
Dai, Min& Tang, Dunbing& Zheng, Kun& Cai, Qixiang. 2013. An Improved Genetic-Simulated Annealing Algorithm Based on a Hormone Modulation Mechanism for a Flexible Flow-Shop Scheduling Problem. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-447548
Modern Language Association (MLA)
Dai, Min…[et al.]. An Improved Genetic-Simulated Annealing Algorithm Based on a Hormone Modulation Mechanism for a Flexible Flow-Shop Scheduling Problem. Advances in Mechanical Engineering No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-447548
American Medical Association (AMA)
Dai, Min& Tang, Dunbing& Zheng, Kun& Cai, Qixiang. An Improved Genetic-Simulated Annealing Algorithm Based on a Hormone Modulation Mechanism for a Flexible Flow-Shop Scheduling Problem. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-447548
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-447548