Heuristic Evolution with Genetic Programming for Traveling Thief Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{Mei:2015:CEC,

• author = "Yi Mei and Xiaodong Li and Flora Salim and Xin Yao",
• title = "Heuristic Evolution with Genetic Programming for Traveling Thief Problem",
• booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015)",
• year = "2015",
• editor = "Yadahiko Murata",
• pages = "2753--2760",
• address = "Sendai, Japan",
• month = "25-28 " # may,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, Traveling thief problem, memetic algorithm, interdependent optimization",
• isbn13 = "978-1-4799-7491-7",
• URL = "http://homepages.ecs.vuw.ac.nz/~yimei/Papers/CEC2015-MeiLiSalimYao.pdf",
• DOI = "doi:10.1109/CEC.2015.7257230",
• abstract = "In many real-world applications, one needs to deal with a large multi-silo problem with interdependent silos. In order to investigate the interdependency between silos (subproblems), the Traveling Thief Problem (TTP) was designed as a benchmark problem. TTP is a combination of two well-known sub-problems, Travelling Salesman Problem (TSP) and Knapsack Problem (KP). Although each sub-problem has been intensively investigated, the interdependent combination has been demonstrated to be challenging, and cannot be solved by simply solving the sub-problems separately. The Two-Stage Memetic Algorithm (TSMA) is an effective approach that has decent solution quality and scalability, which consists of a tour improvement stage and an item picking stage. Unlike the traditional TSP local search operators adopted in the former stage, the heuristic for the latter stage is rather intuitive. To further investigate the effect of item picking heuristic, Genetic Programming (GP) is employed to evolve a gain function and a picking function, respectively. The resultant two heuristics were tested on some representative TTP instances, and showed competitive performance, which indicates the potential of evolving more promising heuristics for solving TTP more systematically by GP.",
• notes = "1300 hrs 15200 CEC2015",

}

Genetic Programming entries for Yi Mei Xiaodong Li Flora Salim Xin Yao

Citations