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Open AccessArticle

Two-Machine Job-Shop Scheduling Problem to Minimize the Makespan with Uncertain Job Durations

United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova Street 6, 220012 Minsk, Belarus
Department of Automated Production Management Systems, Belarusian State Agrarian Technical University, Nezavisimosti Avenue 99, 220023 Minsk, Belarus
Department of Electronic Computing Machines, Belarusian State University of Informatics and Radioelectronics, P. Brovki Street 6, 220013 Minsk, Belarus
Author to whom correspondence should be addressed.
Algorithms 2020, 13(1), 4;
Received: 30 October 2019 / Revised: 14 December 2019 / Accepted: 16 December 2019 / Published: 20 December 2019
(This article belongs to the Special Issue Exact and Heuristic Scheduling Algorithms)
We study two-machine shop-scheduling problems provided that lower and upper bounds on durations of n jobs are given before scheduling. An exact value of the job duration remains unknown until completing the job. The objective is to minimize the makespan (schedule length). We address the issue of how to best execute a schedule if the job duration may take any real value from the given segment. Scheduling decisions may consist of two phases: an off-line phase and an on-line phase. Using information on the lower and upper bounds for each job duration available at the off-line phase, a scheduler can determine a minimal dominant set of schedules (DS) based on sufficient conditions for schedule domination. The DS optimally covers all possible realizations (scenarios) of the uncertain job durations in the sense that, for each possible scenario, there exists at least one schedule in the DS which is optimal. The DS enables a scheduler to quickly make an on-line scheduling decision whenever additional information on completing jobs is available. A scheduler can choose a schedule which is optimal for the most possible scenarios. We developed algorithms for testing a set of conditions for a schedule dominance. These algorithms are polynomial in the number of jobs. Their time complexity does not exceed O ( n 2 ) . Computational experiments have shown the effectiveness of the developed algorithms. If there were no more than 600 jobs, then all 1000 instances in each tested series were solved in one second at most. An instance with 10,000 jobs was solved in 0.4 s on average. The most instances from nine tested classes were optimally solved. If the maximum relative error of the job duration was not greater than 20 % , then more than 80 % of the tested instances were optimally solved. If the maximum relative error was equal to 50 % , then 45 % of the tested instances from the nine classes were optimally solved. View Full-Text
Keywords: scheduling; uncertain duration; flow-shop; job-shop; makespan criterion scheduling; uncertain duration; flow-shop; job-shop; makespan criterion
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Sotskov, Y.N.; Matsveichuk, N.M.; Hatsura, V.D. Two-Machine Job-Shop Scheduling Problem to Minimize the Makespan with Uncertain Job Durations. Algorithms 2020, 13, 4.

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