Agent-Based Goal Programming — Hybrid simulation-optimization with decentralized agents and multi-goal satisfaction
Agent-Based Goal Programming (ABGP) integrates agent-based simulation with goal programming optimization to model systems where multiple autonomous decision-makers pursue competing, prioritized goals. It enables researchers to study how decentralized, adaptive behavior at the agent level leads to system-level outcomes measured against predefined targets, capturing both emergence and multi-criteria satisfaction simultaneously.
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来源
- Charnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138-151. DOI: 10.1287/mnsc.1.2.138 ↗
- Macal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4(3), 151-162. DOI: 10.1057/jos.2010.3 ↗
如何引用本页
ScholarGate. (2026, June 3). Agent-Based Goal Programming — Hybrid simulation-optimization with decentralized agents and multi-goal satisfaction. ScholarGate. https://scholargate.app/zh/simulation/agent-based-goal-programming
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