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Pemrograman Tujuan Berbasis Agen×Pemrograman Tujuan Multi-Objektif×
BidangSimulasiSimulasi
KeluargaProcess / pipelineProcess / pipeline
Tahun asal1990s-2000s (hybrid integration)1961
PencetusCharnes, Cooper (GP); Schelling, Holland (ABM foundations)Charnes, A. and Cooper, W. W.
TipeHybrid simulation-optimizationMathematical programming / multi-criteria optimization
Sumber perintisCharnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138-151. DOI ↗Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 978-0471148258
AliasABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal ProgrammingMOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming
Terkait54
RingkasanAgent-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.Multi-Objective Goal Programming (MOGP) is a mathematical programming technique that simultaneously pursues several aspirational targets by minimizing weighted deviations from each goal. Rooted in Charnes and Cooper's original goal programming framework (1961), MOGP extends it to handle multiple competing objectives, making it indispensable in operations research, supply chain design, resource allocation, and policy analysis where decision-makers must satisfy — or come close to — multiple conflicting requirements at once.
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ScholarGateBandingkan metode: Agent-based goal programming · Multi-objective goal programming. Diakses 2026-06-15 dari https://scholargate.app/id/compare