Breakout Local Search for the Travelling Salesman Problem

The travelling salesman problem (TSP), a famous NP-hard combinatorial optimisation problem (COP), consists of finding a minimum length tour that visits n cities exactly once and comes back to the starting city. This paper presents a resolution of the TSP using the breakout local search metaheuristic algorithm (BLS), which is based on the iterated local search (ILS) framework and improves it by introducing some fundamental features of several well-established metaheuristics such as tabu search (TS) and variable neighbourhood search (VNS). BLS moves from a local optimum of a neighbourhood to another by applying perturbation jumps whose type and number are determined adaptively. It has already been applied to many COP and gives good results. This innovative hybridisation resolved well 41 instances from the commonly used benchmark library TSPLIB. The high quality of experimental results shows the competitiveness of the proposed algorithm compared to other algorithms based on local search

2Zero project D5.1 Modelling And Simulation Report

This report summarises the work in the Modelling and Simulation Work Package, WP 2, of the 2Zero project (funded by Innovate UK, grant agreement number 74829) under UKRI’s Future Flight Challenge Fund. It discusses the simulation that was built, how it works, its purpose, how it was used within the project, the results of doing so, and the various lessons learned from the project

A Memetic Algorithm Based on Breakout Local Search for the Generalized Traveling Salesman Problem

The Traveling Salesman Problem (TSP) is one of the most popular Combinatorial Optimization Problem. It is well solicited for the large variety of applications that it can solve, but also for its difficulty to find optimal solutions. One of the variants of the TSP is the Generalized TSP (GTSP), where the TSP is considered as a special case which makes the GTSP harder to solve. We propose in this paper a new memetic algorithm based on the well-known Breakout Local Search (BLS) metaheuristic to provide good solutions for GTSP instances. Our approach is competitive compared to other recent memetic algorithms proposed for the GTSP and gives at the same time some improvements to BLS to reduce its runtime

Introducing a hash function for the travelling salesman problem for differentiating solutions

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