Social cognitive optimization for nonlinear programming problems

2003/06/26 by Xiaofeng Xie, Wen-Jun Zhang, Zhi-Lian Yang · 4 citations
Computer Science · #AI-based Problem Solving and Planning #Evolutionary Algorithms and Applications #Metaheuristic Optimization Algorithms Research

paper · doi:10.1109/icmlc.2002.1174487

openalex publication_date 2003/06/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

Social cognitive optimization (SCO) for solving nonlinear programming problems (NLP) is presented based on human intelligence with the social cognitive theory (SCT). Experiments comparing SCO with genetic algorithms on some benchmark functions show that the former can produce high-quality solutions efficiently, even with only one learning agent.

Citations

• Social Cognitive Theory: An Agentic Perspective

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• Social cognitive optimization [wikipedia]