Minimax regret strategies for greenhouse gas abatement: methodology and application

Classical stochastic programming has already been used with large-scale LP models for long-term analysis of energy-environment systems. We propose a Minimax Regret formulation suitable for large-scale linear programming models. It has been experimentally verified that the minimax regret strategy depends only on the extremal scenarios and not on the intermediate ones, thus making the approach computationally efficient. Key results of minimax regret and minimum expected value strategies for Greenhouse Gas abatement in the Province of Quebec, are compared.