Process / pipelineSimulation / optimization

Agent-Based Integer Programming — Hybrid Simulation-Optimization for Discrete Decision Systems

Agent-Based Integer Programming (ABIP) couples the behavioral richness of agent-based modeling with the combinatorial rigor of integer programming. Individual agents pursue local objectives while a global IP solver enforces discrete feasibility constraints, enabling realistic modeling of multi-actor systems where decisions must be integer-valued — such as resource allocation, scheduling, and network design under emergent interaction effects.

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Sources

  1. Wooldridge, M. (2009). An Introduction to MultiAgent Systems (2nd ed.). Wiley. ISBN: 9780470519462
  2. Macal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4(3), 151-162. DOI: 10.1057/jos.2010.3

Related methods

ScholarGateAgent-based integer programming (Agent-Based Integer Programming — Hybrid optimization integrating agent-based modeling with integer programming). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/agent-based-integer-programming