Evolutionary multi-objective optimisation: a bibliometric study. (17th December 2021)

• Record Type: Journal Article
• Authors: Abdeljaouad, Mohamed Amine; Bahroun, Zied; Bechikh, Slim
• Is Part Of: International journal of mathematics in operational research. Volume 20:Number 3(2021)
• Page Start: 328
• Page End: 354
• Publication Date: 2021-12-17
• Subjects: bibliometric -- evolutionary -- metaheuristic -- multi-objective -- network analysis; Operations research -- Mathematical models -- Periodicals; Operations research -- Mathematics -- Periodicals; Decision making -- Mathematical models -- Periodicals; 658.4033
• Languages: English
• ISSNs: 1757-5850

Abstract

Evolutionary algorithms are among the most popular methods for solving optimisation problems. The use of metaheuristics emulating the natural evolution of living organisms dates back to the 1970s. In this study, a particular focus is put to use these evolutionary techniques to solve multi-objective optimisation problems. Based on a bibliometric and network analysis, the paper provides a review of 5, 549 scientific publications (journal articles and book chapters) on the field before June 2019. The top contributing authors, journals, organisations, and countries are identified, as well as the most used key-words related to the topic. Then, the most influential papers are compared on the basis of citations and PageRank. The established research clusters and emergent research directions are also discussed.