Intuitionistic Fuzzy Hybrid Discrete Particle Swarm Optimization for Solving Travelling Salesman Problem

DOI

10.2991/icamcs-16.2016.156How to use a DOI?

Keywords

intuitionistic fuzzy set, membership degree function, identical factor, the local optima, elitist reserving

Abstract

An intuitionistic fuzzy hybrid discrete particle swarm optimization (IF-HDPSO) is proposed for solving travelling salesman problem (TSP). By defining intuitionistic fuzzy charisma function, the IF-HDPSO algorithm exploits some other individuals to participate in the updates of velocity and position except the best one. In addition, the PSO identical factor function is defined to adjust inertia weight and learning operator adaptively, so the IF-HDPSO can explore the whole optimal solution quickly. Furthermore, an adaptive genetic algorithm based on elitist reserving strategy is developed, and combine it with PSO to reduce the probability of being trapped in the local optima and premature convergence. The simulation results indicate IF-HDPSO perform better on precision, iteration number and computational robustness.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Hai-Tao Mei
AU  - Ji-Xue Hua
AU  - Yi Wang
AU  - Tong Wen
PY  - 2016/06
DA  - 2016/06
TI  - Intuitionistic Fuzzy Hybrid Discrete Particle Swarm Optimization for Solving Travelling Salesman Problem
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 765
EP  - 771
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.156
DO  - 10.2991/icamcs-16.2016.156
ID  - Mei2016/06
ER  -