Runtime analysis of some hybrid algorithms

• Published in: Neural computing & applications Vol. 35; no. 19; pp. 14153 - 14167
• Main Authors: Lai, Xinsheng, Zhou, Yuren
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2023; Springer Nature B.V
• Subjects: Algorithms; Approximation; Artificial Intelligence; Boolean; Boolean functions; Combinatorial analysis; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Investigations; Mutation; Optimization; Original Article; Probability and Statistics in Computer Science; Run time (computers); Traveling salesman problem; Upper bounds; Runtime; Performance analysis; Hybrid algorithm; Combinatorial optimization problem
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-023-08388-1

A hybrid algorithm combines two or more individual algorithms in order to integrate the advantages of these individual algorithms. In recent years, a huge number of hybrid algorithms have been proposed, and their efficiencies have been demonstrated by experimental studies. However, few theoretical results that support the experimental conclusions are available. In this paper, we focus on theoretical investigation about the efficiency of hybrid algorithms for combinatorial optimization problems. We first analyze the runtime of three specific hybrid algorithms and their component algorithms on two instances. One is a well-known pseudo-Boolean function, and the other is an instance of a classical combinatorial optimization problem. We then theoretically investigate the relationship between the upper bounds of the expected runtime of three kinds of general hybrid algorithms and their component algorithms.