Two-agent two-machine flowshop scheduling with learning effects to minimize the total completion time |
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| Affiliation: | 1. The University of Sydney Business School, Sydney, NSW 2006, Australia;2. Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel;3. Operations Management Area, DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada |
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| 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. |
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| Keywords: | Scheduling Total completion time Two agent Two-machine flowshop Learning effects |
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