Minimization of Total Weighted Earliness and Tardiness using PSO for One Machine Scheduling
نویسنده
چکیده
A novel algorithm for one machine scheduling to minimize total weighted earliness and tardiness using particle swarm optimization is proposed. Existing techniques face challenges such as job size limitations increase in computational time and inaccurate solutions. To overcome these challenges the proposed work implements Meta-Heuristic based particle swarm optimization to optimize the total weighted tardiness and earliness of jobs. The positions of the particles are arranged according to smallest position value which transforms the particle positions into job permutations. The algorithm has been tested for the various job sizes and the performance measures for fitness and computation time have been analyzed for the worst, average and best cases.
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حل مسئله زمان بندی ماشینهای موازی نامرتبط با اهداف کل زودکرد وزنی و کل دیرکرد وزنی با استفاده از الگوریتم جستجوی پراکنده چند هدفه
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