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What is Multiobjective Programming (MOP)

Handbook of Research on Autopoiesis and Self-Sustaining Processes for Organizational Success
Multi-objective programming, also named as multi-objective optimization, vector optimization, or Pareto optimization. The MOP is a branch of operational research. The conflicting objectives form the Pareto frontier (or trade-off frontier) in the objective space. The optimal solution is considered in the presence of a trade-off frontier between two or more conflicting objectives.
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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