An iterated greedy algorithm for the hybrid flowshop problem with makespan criterion
Loading...

Date
2014
Authors
Damla Kizilay
M. Fatih Tasgetiren
Quanke Pan
Ling Wang
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
The main contribution of this paper is to present some novel constructive heuristics for the the hybrid flowshop scheduling (HFS) problem with the objective of minimizing the makespan for the first time in the literature. We developed the constructive heuristics based the profile fitting heuristic by exploiting the waiting time feature of the HFS problem. In addition we also developed an IG algorithm with a simple insertion based local search for the first time in the literature too. The benchmark suite developed for the HFS problem are used to test the performance of the constructive heuristics and the IG algorithm. The computational results show that constructive heuristics developed were able to further improve the traditional NEH heuristics for the HFS problem with makespan criterion. Furthermore with a very short CPU times of 50nm miliseconds the performance of the IG algorithm was very competitive to the PSO and AIS algorithms that were run for 1600 seconds. © 2018 Elsevier B.V. All rights reserved.
Description
Keywords
Logistics, Benchmark Suites, Computational Results, Hybrid Flow Shop Problem, Hybrid Flow-shop Scheduling (hfs), Iterated Greedy Algorithm, Makespan Criterion, Profile Fitting, Waiting-time, Benchmarking, Logistics, Benchmark suites, Computational results, Hybrid flow shop problem, Hybrid flow-shop scheduling (HFS), Iterated greedy algorithm, Makespan criterion, Profile fitting, Waiting-time, Benchmarking
Fields of Science
0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
11
Source
2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems CIPLS 2014
Volume
Issue
Start Page
16
End Page
23
Collections
PlumX Metrics
Citations
CrossRef : 1
Scopus : 19
Captures
Mendeley Readers : 11
Google Scholar™


