Authors:
Xingye Dong
1
;
Maciek Nowak
2
;
Ping Chen
3
and
Houkuan Huang
4
Affiliations:
1
Beijing Jiaotong University and Loyola University, China
;
2
Loyola University, United States
;
3
NanKai University, China
;
4
Beijing Jiaotong University, China
Keyword(s):
Scheduling, Permutation Flow Shop, Total Flow Time, Iterated Local Search, Neighborhood.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Planning and Scheduling
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
Flow shop scheduling minimizing total flow time is a famous combinatorial optimization problem. Many algorithms have been proposed to solve it. Among them, iterated local search (ILS) is a simple, efficient and effective one. However, in existing ILS, one basic insertion neighborhood is generally used, greatly limiting
the search space. In this work, an enhanced iterated local search (EILS) is proposed, using a hybrid of insertion and swap neighborhoods. The perturbation method also plays an important role in ILS. Two perturbation methods, the insertion method and a destruction and construction heuristic are tested in this paper. Both perform significantly better in comparison to three state of the art algorithms, indicating that the hybrid use of insertion and swap neighborhoods is effective for the discussed problem. However, there is no significant difference between the destruction and construction and the insertion perturbation methods.