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

TL;DR

This paper introduces a new memetic algorithm based on Breakout Local Search to effectively solve the challenging Generalized Traveling Salesman Problem, demonstrating competitive performance and improved runtime efficiency.

Contribution

The paper presents a novel memetic algorithm combining BLS for GTSP, enhancing solution quality and reducing computational time compared to existing methods.

Findings

Competitive results against recent memetic algorithms

Improved runtime efficiency of BLS-based approach

Effective solutions for large GTSP instances

Abstract

The Travelling 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.