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Agent-Based Goal Programming×Stokastisk målprogrammering×
ÄmnesområdeSimuleringSimulering
FamiljProcess / pipelineProcess / pipeline
Ursprungsår1990s-2000s (hybrid integration)1968
UpphovspersonCharnes, Cooper (GP); Schelling, Holland (ABM foundations)Contini, B. (building on Charnes & Cooper's chance-constrained programming)
TypHybrid simulation-optimizationStochastic multi-goal optimization
UrsprungskällaCharnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138-151. DOI ↗Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗
AliasABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal ProgrammingSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
Närliggande56
SammanfattningAgent-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.Stochastic Goal Programming (SGP) extends classical goal programming to handle uncertainty in goal targets, constraint coefficients, or right-hand-side parameters. By incorporating probabilistic constraints and stochastic objective components, it finds solutions that satisfy multiple goals at acceptable probability levels, making it suitable for decision problems where data are inherently uncertain or variable.
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ScholarGateJämför metoder: Agent-based goal programming · Stochastic Goal Programming. Hämtad 2026-06-15 från https://scholargate.app/sv/compare