Process / pipelineSimulation / optimization

Robust Goal Programming — Achieving Multiple Targets Under Uncertainty

Robust Goal Programming (RGP) extends classical goal programming to handle uncertain or ambiguous model parameters. Instead of minimizing deviations from crisp targets, it seeks solutions that remain feasible and near-optimal across a range of plausible scenarios or uncertain data realizations. RGP is particularly valuable in planning problems where goals are aspirational and input data carries inherent variability or estimation error.

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Sources

  1. Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 9780471155041
  2. Mulvey, J. M., Vanderbei, R. J., Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations Research, 43(2), 264-281. DOI: 10.1287/opre.43.2.264

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Referenced by

ScholarGateRobust goal programming (Robust Goal Programming). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/robust-goal-programming