COOBBO: a novel opposition-based soft computing algorithm for TSP problems
type: Item
instance of: scholarly article
title: COOBBO: a novel opposition-based soft computing algorithm for TSP problems
zbMATH Open document ID: 1461.90125
author: Qingzheng Xu
author: Lemeng Guo
author: Na Wang
author: Yongjian He
published in: Algorithms
publication date: 2019-03-26T00:00:00Z
review text: Summary: In this paper, we propose a novel definition of opposite path. Its core feature is that the sequence of candidate paths and the distances between adjacent nodes in the tour are considered simultaneously. In a sense, the candidate path and its corresponding opposite path have the same (or similar at least) distance to the optimal path in the current population. Based on an accepted framework for employing opposition-based learning, Oppositional Biogeography-Based Optimization using the Current Optimum, called COOBBO algorithm, is introduced to solve traveling salesman problems. We demonstrate its performance on eight benchmark problems and compare it with other optimization algorithms. Simulation results illustrate that the excellent performance of our proposed algorithm is attributed to the distinct definition of opposite path. In addition, its great strength lies in exploitation for enhancing the solution accuracy, not exploration for improving the population diversity. Finally, by comparing different version of COOBBO, another conclusion is that each successful opposition-based soft computing algorithm needs to adjust and remain a good balance between backward adjacent node and forward adjacent node.
Mathematics Subject Classification ID: 90C27
Mathematics Subject Classification ID: 68W05
zbMATH DE Number: 7042231
zbMATH Keywords: biogeography-based optimization
zbMATH Keywords: opposition-based learning
zbMATH Keywords: traveling salesman problems
zbMATH Keywords: discrete domain
zbMATH Keywords: opposite path
zbMATH Keywords: population diversity
describes a project that uses: TSPLIB
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a7040663
OpenAlex ID: W2076323553
cites work: Oppositional concepts in computational intelligence
cites work: A multi-start opposition-based particle swarm optimization algorithm with adaptive velocity for bound constrained global optimization
cites work: Two Frameworks for Improving Gradient-Based Learning Algorithms
cites work: A diversity maintaining population-based incremental learning algorithm
cites work: TSPLIB—A Traveling Salesman Problem Library
cites work: Exploration and exploitation in evolutionary algorithms: a survey
DOI: 10.3390/A7040663
description: scientific article; zbMATH DE number 7042231