@inproceedings{04d97392bcab45e0a451b30b67d38323,
title = "A solution framework based on packet scheduling and dispatching rule for job-based scheduling problems",
abstract = "Job-based scheduling problems have inherent similarities and relations. However, the current researches on these scheduling problems are isolated and lack references. We propose a unified solution framework containing two innovative strategies: the packet scheduling strategy and the greedy dispatching rule. It can increase the diversity of solutions and help in solving the problems with large solution space effectively. In addition, we propose an improved particle swarm optimization (PSO) algorithm with a variable neighborhood local search mechanism and a perturbation strategy. We apply the solution framework combined with the improved PSO to the benchmark instances of different job-based scheduling problems. Our method provides a self-adaptive technique for various job-based scheduling problems, which can promote mutual learning between different areas and provide guidance for practical applications.",
keywords = "Dispatching rule, Improved PSO, Job-based scheduling, Packet scheduling, Unified solution framework",
author = "Rongrong Zhou and Hui Lu and Jinhua Shi",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 9th International Conference on Swarm Intelligence, ICSI 2018 ; Conference date: 17-06-2018 Through 22-06-2018",
year = "2018",
doi = "10.1007/978-3-319-93818-9\_19",
language = "英语",
isbn = "9783319938172",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "202--211",
editor = "Ying Tan and Qirong Tang and Yuhui Shi",
booktitle = "Advances in Swarm Intelligence - 9th International Conference, ICSI 2018, Proceedings",
address = "德国",
}