Abstract
This paper describes the development of a mixed binary integer programming (BIP) model for scheduling alternative operations in two-machine flow-shop problems with mean tardiness as the criterion. Although the mixed BIP model provides an optimal solution, its variables and constraints increase drastically as the number of jobs increases. Therefore, an optimal solution is not always attainable within the allowable time by solving the mixed BIP model. Consequently, two heuristics suitable for the formulated scheduling problems are proposed. Computational experiments are conducted to test the accuracy and efficiency of the heuristics in generating near optimal solutions for minimising the mean tardiness of jobs.
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