Cosolver2B: An Efficient Local Search Heuristic for the Travelling Thief Problem
This is an incremental improvement for supply chain management and transportation optimization.
The paper tackled the NP-hard Traveling Thief Problem (TTP), a realistic model for routing with packing constraints, by proposing a combined local search algorithm that found new better solutions compared to Random Local Search and Evolutionary Algorithm.
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.