A Unifying Survey of Reinforced, Sensitive and Stigmergic Agent-Based Approaches for E-GTSP

TL;DR

This paper surveys various agent-based algorithms, including ant-based models, designed to solve the NP-hard E-GTSP, a variant of the Traveling Salesman Problem with specific cluster constraints.

Contribution

It provides a comprehensive overview of agent-based approaches tailored for E-GTSP, highlighting their properties and potential for solving complex combinatorial problems.

Findings

Agent-based methods effectively solve E-GTSP instances.

Ant-based models show promising results for cluster constraints.

The survey identifies key properties and variations of agent algorithms.

Abstract

The Generalized Traveling Salesman Problem (GTSP) is one of the NP-hard combinatorial optimization problems. A variant of GTSP is E-GTSP where E, meaning equality, has the constraint: exactly one node from a cluster of a graph partition is visited. The main objective of the E-GTSP is to find a minimum cost tour passing through exactly one node from each cluster of an undirected graph. Agent-based approaches involving are successfully used nowadays for solving real life complex problems. The aim of the current paper is to illustrate some variants of agent-based algorithms including ant-based models with specific properties for solving E-GTSP.