Myopic Heuristics for the Weighted Tardiness Problem on Identical Parallel Machines.
CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
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The authors study the problem of scheduling jobs on parallel identical machines to minimize weighted tardiness. There are no known heuristics for this problem. The heuristic rule developed is simple. It can be used in the dispatch mode which makes it very practical. Characterizations of optimal solutions are presented. Computational results show that the myopic heuristic performed well vis-a-vis other rules such as the Earliest Due Date Rule, Weighted Shortest Processing Time Rule and two versions of Montagnes Rule. Reported are computational results and also the performance of the heuristic in comparison to high computational benchmarks. Author
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