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Operations Research Transactions >

2026 , Vol. 30 >Issue 1: 1 - 23

DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2026.01.001

A survey on research advances in consensus-based optimization algorithm

  • WEI Jiazhen ,
  • BIAN Wei
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  • School of Mathematics, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China

Received date: 2025-04-06

  Online published: 2026-03-16

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Abstract

Global optimization problems have widespread applications across various fields such as scientific research, engineering, economics, and artificial intelligence. Consensus-based optimization algorithm is a class of multi-agent, meta-heuristic and derivative-free algorithms. It is designed to solve global nonsmooth and nonconvex optimization problems, while also being conducive to theoretical analysis and algorithm implementation. In this paper, we first introduce the fundamental principles and analytical results of the original algorithm. Subsequently, the latest development of the consensus-based optimization algorithms and their variants are discussed in detail. And the applications in fields such as machine learning and image processing are briefly described. Finally, we explore future research directions across three key areas: theoretical innovation, algorithm design, and application expansion.

Key words： global optimization; nonsmooth and nonconvex optimization; consensus-base optimization algorithm; swarm intelligence algorithm; finite particle system

Cite this article

WEI Jiazhen , BIAN Wei . A survey on research advances in consensus-based optimization algorithm[J]. Operations Research Transactions, 2026 , 30(1) : 1 -23 . DOI: 10.15960/j.cnki.issn.1007-6093.2026.01.001

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