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ΠεδίοΠροσομοίωσηΠροσομοίωση
ΟικογένειαProcess / pipelineProcess / pipeline
Έτος προέλευσης1990s-2000s (hybrid integration)1968
ΔημιουργόςCharnes, Cooper (GP); Schelling, Holland (ABM foundations)Contini, B. (building on Charnes & Cooper's chance-constrained programming)
ΤύποςHybrid simulation-optimizationStochastic multi-goal optimization
Θεμελιώδης πηγήCharnes, 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 ↗
Εναλλακτικές ονομασίεςABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal ProgrammingSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
Συναφείς56
ΣύνοψηAgent-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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ScholarGateΣύγκριση μεθόδων: Agent-based goal programming · Stochastic Goal Programming. Ανακτήθηκε στις 2026-06-15 από https://scholargate.app/el/compare