Improving Hyper-heuristic Performance for Job Shop Scheduling Problems Using Neural Networks

Lara-Cárdenas, Erick; Sánchez-Díaz, Xavier; Amaya, Iván; Ortíz-Bayliss, José Carlos

doi:10.1007/978-3-030-33749-0_13

Cited by 4 publications

(1 citation statement)

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“…They reported that such a model was able to outperform a synthetic Oracle, obtained from several low-level heuristics, in almost 30%. Besides them, Lara-Cárdenas et al utilized Neural Networks for boosting the performance of various HHs reported in the literature in JSSP applications [78].…”

Section: ) Job Shop Schedulingmentioning

confidence: 99%

A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems

et al. 2020

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Hyper-heuristics aim at interchanging different solvers while solving a problem. The idea is to determine the best approach for solving a problem at its current state. This way, every time we make a move it gets us closer to a solution. The problem changes; so does its state. As a consequence, for the next move, a different solver may be invoked. Hyper-heuristics have been around for almost 20 years. However, combinatorial optimization problems date from way back. Thus, it is paramount to determine whether the efforts revolving around hyper-heuristic research have been targeted at the problems of the highest interest for the combinatorial optimization community. In this work, we tackle such an endeavor. We begin by determining the most relevant combinatorial optimization problems, and then we analyze them in the context of hyper-heuristics. The idea is to verify whether they remain as relevant when considering exclusively works related to hyper-heuristics. We find that some of the most relevant problem domains have also been popular for hyper-heuristics research. Alas, others have not and few efforts have been directed towards solving them. We identify the following problem domains, which may help in furthering the impact of hyper-heuristics: Shortest Path, Set Cover, Longest Path, and Minimum Spanning Tree. We believe that focusing research on ways for solving them may lead to an increase in the relevance and impact that hyperheuristics have on combinatorial optimization problems.

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Section: ) Job Shop Schedulingmentioning

confidence: 99%