A single-machine learning effect scheduling problem with release times
In this paper, we investigate a single-machine problem with the learning effect and release times where the objective is to minimize the makespan. A branch-and-bound algorithm incorporating with several dominance properties and lower bounds is developed to derive the optimal solution. A heuristic algorithm is proposed to obtain a near-optimal solution. The computational experiments show that the branch-and-bound algorithm can solve instances up to 36 jobs, and the average error percentage of the proposed heuristic is less than 0.11%.
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Volume (Year): 38 (2010)
Issue (Month): 1-2 (February)
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