Abstract
Scheduling with multiple agents and learning effects has attracted growing attention of the scheduling research community. However, scheduling research together with learning, multiple agents and release times considerations is few. This paper considers two-agent single-machine scheduling with a position-based learning effect. The criterion measurement is to minimize the number of the tardy jobs of the first agent subject to the condition that the second agent has no tardy job. A branch-and-bound and a hybrid heuristic are proposed to solve the problem.
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