Christopher Stone
Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs
Stone, Christopher; Hart, Emma; Paechter, Ben
Authors
Abstract
In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heuristics often suffice in this case. However, for many domains, a simple heuristic may not be available, and designing one can require considerable expertise. Noting that a wide variety of problems can be represented as graphs, we describe a system for the automatic generation of constructive heuristics in the form of Python programs by mean of grammatical evolution. The system can be applied seamlessly to different graph-based problem domains, only requiring modification of the fitness function. We demonstrate its effectiveness by generating heuristics for the Travelling Salesman and Multi-Dimensional Knapsack problems. The system is shown to be better or comparable to human-designed heuristics in each domain. The generated heuristics can be used ‘out-of-the-box’ to provide a solution, or to augment existing hyper-heuristic algorithms with new low-level heuristics.
Citation
Stone, C., Hart, E., & Paechter, B. (2018). Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. In Applications of Evolutionary Computation (578-593). https://doi.org/10.1007/978-3-319-77538-8_40
Conference Name | 21st International Conference, EvoApplications 2018 |
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Conference Location | Parma, Italy |
Start Date | Apr 4, 2018 |
End Date | Apr 6, 2018 |
Acceptance Date | Jan 3, 2018 |
Online Publication Date | Mar 8, 2018 |
Publication Date | 2018 |
Deposit Date | Aug 20, 2018 |
Electronic ISSN | 1611-3349 |
Volume | 10784 |
Pages | 578-593 |
Series Title | Lecture Notes in Computer Science |
Series ISSN | 0302-9743 |
Book Title | Applications of Evolutionary Computation |
ISBN | 9783319775371; 9783319775388 |
DOI | https://doi.org/10.1007/978-3-319-77538-8_40 |
Keywords | heuristics, grammatical evolution, combinatorial optimisation |
Public URL | http://researchrepository.napier.ac.uk/Output/1281618 |
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