Abstract
We study a two-agent scheduling problem in a two-machine permutation flowshop with learning effects. The objective is to minimize the total completion time of the jobs from one agent, given that the maximum tardiness of the jobs from the other agent cannot exceed a bound. We provide a branch-and-bound algorithm for the problem. In addition, we present several genetic algorithms to obtain near-optimal solutions. Computational results indicate that the algorithms perform well in either solving the problem or efficiently generating near-optimal solutions.
Original language | English |
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Pages (from-to) | 580-589 |
Number of pages | 10 |
Journal | Computers and Industrial Engineering |
Volume | 87 |
DOIs | |
Publication status | Published - 29 Jun 2015 |
Keywords
- Learning effects
- Scheduling
- Total completion time
- Two agent
- Two-machine flowshop
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)