Synthesis of Mathematical Programming Constraints with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Pawlak:2017:EuroGP,

• author = "Tomasz P. Pawlak and Krzysztof Krawiec",
• title = "Synthesis of Mathematical Programming Constraints with Genetic Programming",
• booktitle = "EuroGP 2017: Proceedings of the 20th European Conference on Genetic Programming",
• year = "2017",
• month = "19-21 " # apr,
• editor = "Mauro Castelli and James McDermott and Lukas Sekanina",
• series = "LNCS",
• volume = "10196",
• publisher = "Springer Verlag",
• address = "Amsterdam",
• pages = "178--193",
• organisation = "species",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-55695-6",
• DOI = "doi:10.1007/978-3-319-55696-3_12",
• abstract = "We identify a novel application of Genetic Programming to automatic synthesis of mathematical programming (MP) models for business processes. Given a set of examples of states of a business process, the proposed Genetic Constraint Synthesis (GenetiCS) method constructs well-formed constraints for an MP model. The form of synthesized constraints (e.g., linear or polynomial) can be chosen accordingly to the nature of the process and the desired type of MP problem. In experimental part, we verify syntactic and semantic fidelity of the synthesized models to the actual benchmark models of varying complexity. The obtained symbolic models of constraints can be combined with an objective function of choice, fed into an off- shelf MP solver, and optimized.",
• notes = "Part of \cite{Castelli:2017:GP} EuroGP'2017 held inconjunction with EvoCOP2017, EvoMusArt2017 and EvoApplications2017",

}

Genetic Programming entries for Tomasz Pawlak Krzysztof Krawiec

Citations