A Scientometric Analysis of Multiobjective Optimization Research

Abstract

Multiobjective optimization (MOO) has been adopted in many areas of research where optimal decisions must be made in the presence of trade-offs between two or more conflicting objectives. MOO assists researchers and practitioners to optimize multiobjective simultaneously. Despite the volume amplification of the MOO research in many scientific and engineering fields, there is not a single analytical study addressing the evolution and impact of this topic. Thus, the present study conducts a scientometric analysis to anatomize the publications on MOO research, and their intellectual structure and networking. The study offers a comprehensive analysis of the research by analyzing and identifying the advancement, growth, active contributors, influential journals, and seminal documents. It also visualizes the intellectual network through mapping publications' co-citation analysis. Through an in-depth analysis of MOO research evolution and pathways, this study provides researchers and practitioners with a better understanding of the development trends that have emerged in this field over the past three decades, which can also be a guidance for future research. As the first scientometric investigation of MOO research, the present study offers several implications for future research.