| Summary: | 碩士 === 逢甲大學 === 工業工程與系統管理學研究所 === 98 === Scheduling n identical jobs on m uniform parallel machines to minimize scheduling criteria is very common in practice. The case of identical jobs within a batch is common in manufacturing systems, where the products have identical designs or processing times on the same machine. Also, factories often buy new equipment but retain their slower, older equipment; this results in machines that have different processing speeds. In this research, we proposed several linear programming (LP) models and efficient algorithms to solve the problems of scheduling identical jobs on uniform parallel machines to minimize several regular performance measures individually. Moreover, some extensions of this problem, such as jobs may be required to meet a common due date, or jobs may be restricted by unequal release dates, or when jobs preemptions are allowed are also considered. Performance measures include makespan, total completion time, total weighted completion time, total tardiness, total weighted tardiness, number of tardy jobs, weighted number of tardy jobs, total earliness and tardiness, total weighted earliness and tardiness, and maximum lateness. Computational results showed that proposed LP models can find optimal solutions with equal or less time complexities when compared to other existing LP models. Moreover, proposed algorithms outperform other existing algorithms in terms of solution quality.
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