<abstract xmlns="http://www.w3.org/1999/xhtml"><p>A scheduling problem in considered on unrelated machines with the goal of total late work minimization, in which the late work of a job means the late units executed after its due date. Due to the NP-hardness of the problem, we propose two meta-heuristic algorithms to solve it, namely, a tabu search (TS) and a genetic algorithm (GA), both of which are equipped with the techniques of initialization, iteration, as well as termination. The performances of the designed algorithms are verified through computational experiments, where we show that the GA can produce better solutions but with a higher time consumption. Moreover, we also analyze the influence of problem parameters on the performances of these meta-heuristics.</p></abstract>

A scheduling problem in considered on unrelated machines with the goal of total late work minimization, in which the late work of a job means the late units executed after its due date. Due to the NP-hardness of the problem, we propose two meta-heuristic algorithms to solve it, namely, a tabu search (TS) and a genetic algorithm (GA), both of which are equipped with the techniques of initialization, iteration, as well as termination. The performances of the designed algorithms are verified through computational experiments, where we show that the GA can produce better solutions but with a higher time consumption. Moreover, we also analyze the influence of problem parameters on the performances of these meta-heuristics.

Two Meta–Heuristic Algorithms for Scheduling on Unrelated Machines with the Late Work Criterion

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A scheduling problem in considered on unrelated machines with the goal of total late work minimization, in which the late work of a job means the late units...

Two Meta–Heuristic Algorithms for Scheduling on Unrelated Machines with the Late Work Criterion

Published Online: Sep 29, 2020

Page range: 573 - 584

Received: Feb 20, 2020

Accepted: Jul 02, 2020

DOI: https://doi.org/10.34768/amcs-2020-0042

Keywords
late work minimization, unrelated machines, tabu search, genetic algorithm

© 2020 Wen Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Two Meta–Heuristic Algorithms for Scheduling on Unrelated Machines with the Late Work Criterion

Published Online: Sep 29, 2020

Page range: 573 - 584

Received: Feb 20, 2020

Accepted: Jul 02, 2020

DOI: https://doi.org/10.34768/amcs-2020-0042

Keywordslate work minimization, unrelated machines, tabu search, genetic algorithm

© 2020 Wen Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
late work minimization, unrelated machines, tabu search, genetic algorithm