Application of optimized multi-criteria decision-making in an environmental impact assessment study

Abstract

In Multi-Criteria Decision-Making (MCDM) procedures like Analytical Hierarchy Process (AHP), the aggregate impact of a decision is expressed as a numerical score, with a higher score indicating aggregate positive impact of the decision on various impacted parameters or "impact-factors". In case the aggregate score is unsatisfactory, mitigation measures must be incorporated to lessen the adverse impact of the decision on one or more adversely impacted-factors, thus increasing the score. Incorporation of mitigation measures for each impact-factor is associated with a corresponding cost, which vary with the extent of mitigation proposed. Under the circumstances, questions regarding the extent of mitigation required for each impact-factor in order to obtain, (a) a target aggregate mitigation at minimum mitigation cost, or (b) the maximum aggregate mitigation for a fixed mitigation cost, may be asked. Algorithms incorporating integer-programming techniques have been presented in this paper for the above purpose. These algorithms have been implemented and tested using a typical Environmental Impact Assessment (EIA) problem.