Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs

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@InProceedings{Stone:2018:evoApplications,

• author = "Christopher Stone and Emma Hart and Ben Paechter",
• title = "Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs",
• booktitle = "21st International Conference on the Applications of Evolutionary Computation, EvoINDUSTRY 2018",
• year = "2018",
• editor = "Kevin Sim and Neil Urquhart",
• series = "LNCS",
• volume = "10784",
• publisher = "Springer",
• pages = "578--593",
• address = "Parma, Italy",
• month = "4-6 " # apr,
• organisation = "Species",
• keywords = "genetic algorithms, genetic programming, Grammatical evolution, Combinatorial optimisation, Generative hyper-heuristics, Combinatorial geometry",
• isbn13 = "978-3-319-77537-1",
• DOI = "doi:10.1007/978-3-319-77538-8_40",
• 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.",
• notes = "EvoApplications2018 held in conjunction with EuroGP'2018 EvoCOP2018 and EvoMusArt2018 http://www.evostar.org/2018/cfp_evoapps.php",

}

Genetic Programming entries for Christopher Stone Emma Hart Ben Paechter

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