English

Cosolver2B: An Efficient Local Search Heuristic for the Travelling Thief Problem

Artificial Intelligence 2016-03-25 v1 Data Structures and Algorithms Neural and Evolutionary Computing

Abstract

Real-world problems are very difficult to optimize. However, many researchers have been solving benchmark problems that have been extensively investigated for the last decades even if they have very few direct applications. The Traveling Thief Problem (TTP) is a NP-hard optimization problem that aims to provide a more realistic model. TTP targets particularly routing problem under packing/loading constraints which can be found in supply chain management and transportation. In this paper, TTP is presented and formulated mathematically. A combined local search algorithm is proposed and compared with Random Local Search (RLS) and Evolutionary Algorithm (EA). The obtained results are quite promising since new better solutions were found.

Keywords

Cite

@article{arxiv.1603.07051,
  title  = {Cosolver2B: An Efficient Local Search Heuristic for the Travelling Thief Problem},
  author = {Mohamed El Yafrani and Belaïd Ahiod},
  journal= {arXiv preprint arXiv:1603.07051},
  year   = {2016}
}

Comments

12th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA) 2015. November 17-20, 2015

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