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What is Multiobjective Evolutionary Algorithm (MOEA)

Handbook of Research on Autopoiesis and Self-Sustaining Processes for Organizational Success
MOEA means an evolutionary algorithm designed to resolve the MOP problem by approximating the Pareto optimum for conflicting objectives. Any algorithm that can evolve the objective value to its optimum is an evolutionary algorithm. For example, Neural Networks, Genetic Algorithms, and Particle Swarm Optimization belong to Evolutionary Algorithms (EAs) and suitable for MOEA.
Published in Chapter:
Social Network Analysis: Self-Organizing Map and WINGS by Multiple-Criteria Decision Making
Yuh-Wen Chen (Da-Yeh University, Taiwan)
DOI: 10.4018/978-1-7998-6713-5.ch008
Abstract
Social network analysis (SNA) is an attractive problem for a long time when social communities were popular since 2010. Scholars like to explore the meaning behind the numerous interactions generated at these social media sites. The primary and essential issue of SNA is to monitor, estimate, and engage the potential influencers who are most relevant and active to network. If we can analyze the social network this way, business enterprises could use minimal efforts to sustain the activity of influential users, improve sales, and enhance their reputations. In this chapter, a research framework based on multiple-criteria decision making (MCDM) is proposed. The authors will show how scholars could use dynamic self-organizing map (SOM) based on multiple-objective evolving algorithm (MOEA) and static weighted influence non-linear gauge system (WINGS) to analyze a social network. Finally, comparisons are made between the innovative approaches and the methods in tradition.
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