Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Многокритериално моделиране, базирано на агенти× | Многокритериално системно динамично моделиране× | |
|---|---|---|
| Област | Симулационно моделиране | Симулационно моделиране |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2001-2006 | 1961 (SD); multi-objective extensions from 1990s onward |
| Създател≠ | Deb, K.; Tesfatsion, L. et al. | Forrester, J. W. (System Dynamics); multi-objective extension by various authors |
| Тип≠ | Simulation-optimization hybrid | Simulation / optimization hybrid |
| Основополагащ източник≠ | Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester. ISBN: 9780471873396 | Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. ISBN: 978-0-07-231135-8 |
| Други названия | MO-ABM, Multi-objective ABM, Pareto-based agent-based modeling, Multi-objective agent simulation | MOSD, Multi-criteria SD, Multi-objective SD modeling, System dynamics with multiple objectives |
| Свързани | 4 | 4 |
| Резюме≠ | Multi-Objective Agent-Based Modeling (MO-ABM) couples agent-based simulation with multi-objective optimization to simultaneously optimize several conflicting performance criteria across complex adaptive systems. Autonomous agents interact according to behavioral rules while an optimizer searches for parameter configurations that achieve Pareto-optimal trade-offs among competing system-level goals. | Multi-Objective System Dynamics (MOSD) couples the feedback-loop simulation power of System Dynamics with explicit multi-criteria optimization, enabling analysts to explore how a dynamic system can simultaneously satisfy competing policy goals — such as cost minimization, environmental sustainability, and social equity — over time. |
| ScholarGateНабор от данни ↗ |
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