20 Years of Particle Swarm Optimization Strategies for the Vehicle Routing Problem: A Bibliometric Analysis

Abstract

This study uses bibliometric analysis to examine the scientific evolution of particle swarm optimization (PSO) for the vehicle routing problem (VRP) over the past 20 years. Analyses were conducted to discover and characterize emerging trends in the research related to these topics and to examine the relationships between key publications. Through queries of the Web of Science and Scopus databases, the metadata for these particle swarm optimization (PSO) and vehicle routing problem (VRP) solution strategies were compared using bibliographic coupling and co-citation analysis using the Bibliometrix R software package, and secondly with VOSViewer. The bibliometric study’s purpose was to identify the most relevant thematic clusters and publications where PSO and VRP research intersect. The findings of this study can guide future VRP research and underscore the importance of developing effective PSO metaheuristics.

A Systematic Literature Review of the Blood Supply Chain through Bibliometric Analysis and Taxonomy

“…For instance, Danesh et al [31] provide a holistic view of the literature on innovation systems through bibliometric analysis. For the evolution and structure of the implementations of particle swarm optimization to vehicle routing problems, Reong et al [32] utilize the Bibliometrix R software package and VOSViewer. Diaby et al [33] use bibliometric analysis to examine 521 articles on the use of multi-criteria decision analysis in healthcare.…”

Current Trend, Future Direction, and Enablers of e-Waste Management: Bibliometric Analysis and Literature Review

“…Meanwhile, information visualization technology for bibliometric analysis is VOSviewer [12][13][14] and Biblioshiny [15, [16]. Many researchers in various fields use bibliometric analysis, such as in the areas of supply chain management [17,18], blockchain technology [19], urban planning and development [20], text mining [21], environmental, social, and governance [22,23], economy [24], machine learning [25], IoT [26], and municipal waste management [27].…”