I. Introduction

Decision making in real world problems is a complex process as it often involves multiple, conflicting objectives and uncertainties about future projections. This is particularly true when decision makers formulate long term policies towards sustainable development and expect to balance considerations on several competing factors related to economic growth, energy consumption, ecological, social, human capital development, innovation and other related criteria. For example, in developing a growth oriented economic policy the decision maker (DM) must simultaneously balance competing priorities such as minimize taxes, acceptable level of inflation, promote job creation, enhance social welfare, improve population health, along with ecological considerations. GP models allow decision makers to model and analyze multi-criteria problems with multiple, conflicting objectives to decide trade-offs and solution alternatives. GP model was originally introduced by Charnes and Cooper [2] and applied to study problems on optimal executive compensation [3]. Classical GP models are commonly regarded as generalization of linear programming models and have been extensively applied in finance, marketing, engineering, healthcare and many others. We refer the reader to excellent books [4]–[6] and survey articles [7]–[11] highlighting numerous applications of GP models. The popularity of GP models is largely due to the simplicity in mathematical modeling and the ability to solve using standard mathematical programming software. The solutions obtained are not necessarily Pareto optimal (or Pareto efficient) but it is possible to implement strategies (non-dominated) and numerical algorithms to improve the level of efficiency of the current solution.