Abstract
In this paper, the single machine scheduling problem with fuzzy due-dates and controllable processing times is dealt with. The objective is to maximize the “grade of satisfaction” incurred, subject to a total processing cost constraint. The former is a function of the deviations of the jobs completion times from their most desirable due dates. The latter is considered to be a linear function of the jobs compression. The problem is solved via a heuristic approach, which encapsulates concepts from Tabu Search, Genetic Algorithms and Simulated Annealing. Both Complete Enumeration and Branch and Bound techniques are used to evaluate the efficiency of the proposed method.
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