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A novel parallel quantum genetic algorithm for stochastic job shop scheduling. (English) Zbl 1174.90006

The paper investigates the so-called job-shop-scheduling problem, i.e., there is a certain number of jobs that have to be completed on a given number of machines according to a given sequence of operations. The processing times of the jobs on the machines are assumed to be normally distributed. The objective is to find a strategy that minimizes the sum of the expected completion times for the jobs. To solve this problem a parallel quantum genetic algorithm is proposed. The performance of the algorithm is tested by means of three “standard benchmark problems” using simulations.

MSC:

90B36 Stochastic scheduling theory in operations research
68W10 Parallel algorithms in computer science
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