A two-agent one-machine multitasking scheduling problem solving by exact and metaheuristics
| Autor: | Win-Chin Lin, Lamjed Ben Said, Jianyou Xu, Lingfa Lu, Jia-Yang Chen, Ameni Azzouz, Wei-Lun Shen, Chin-Chia Wu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Schedule 021103 operations research Job shop scheduling Computer science Tardiness 0211 other engineering and technologies 02 engineering and technology Upper and lower bounds Computational Mathematics Artificial Intelligence Simulated annealing Genetic algorithm 0202 electrical engineering electronic engineering information engineering Human multitasking 020201 artificial intelligence & image processing Engineering (miscellaneous) Metaheuristic Information Systems |
| Zdroj: | Complex & Intelligent Systems. 8:199-212 |
| ISSN: | 2198-6053 2199-4536 |
| DOI: | 10.1007/s40747-021-00355-4 |
| Popis: | This paper studies a single-machine multitasking scheduling problem together with two-agent consideration. The objective is to look for an optimal schedule to minimize the total tardiness of one agent subject to the total completion time of another agent has an upper bound. For this problem, a branch-and-bound method equipped with several dominant properties and a lower bound is exploited to search optimal solutions for small size jobs. Three metaheuristics, cloud simulated annealing algorithm, genetic algorithm, and simulated annealing algorithm, each with three improvement ways, are proposed to find the near-optimal solutions for large size jobs. The computational studies, experiments, are provided to evaluate the capabilities for the proposed algorithms. Finally, statistical analysis methods are applied to compare the performances of these algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink