方法对比
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| Agent-Based Goal Programming× | 随机目标规划× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s-2000s (hybrid integration) | 1968 |
| 提出者≠ | Charnes, Cooper (GP); Schelling, Holland (ABM foundations) | Contini, B. (building on Charnes & Cooper's chance-constrained programming) |
| 类型≠ | Hybrid simulation-optimization | Stochastic multi-goal optimization |
| 开创性文献≠ | Charnes, 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 ↗ |
| 别名 | ABGP, Agent-Based GP, ABM-GP, Agent-Driven Goal Programming | SGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming |
| 相关≠ | 5 | 6 |
| 摘要≠ | 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. | 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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