Genetic algorithm for minimizing the total weighted completion time scheduling problem with learning and release times

Authors:
Chin-Chia Wu;Peng-Hsiang Hsu;Juei-Chao Chen;Nae-Sheng Wang
Affiliations:
Department of Statistics, Feng Chia University, Taichung, Taiwan, ROC;Department of Statistics, Feng Chia University, Taichung, Taiwan, ROC;Department of Statistics and Information Science & Graduate Institute of Applied Statistics, Fu-Jen Catholic University, Taipei County, Taichung, Taiwan, ROC;Department of Statistics, Feng Chia University, Taichung, Taiwan, ROC
Venue:
Computers and Operations Research
Year:
2011

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Abstract

This paper considers a single-machine problem with the sum-of-processing time based learning effect and release times. The objective is to minimize the total weighted completion times. First, a branch-and-bound algorithm incorporating with several dominance properties and two lower bounds are developed for the optimal solution. Then a genetic heuristic-based algorithm is proposed for a near-optimal solution. Finally, a computational experiment is conducted to evaluate the performances of the proposed algorithms. The results show that the branch-and-bound algorithm can solve instances up to 15 jobs, and the average error percentage of the genetic heuristic algorithm is less than 0.105%.