Extended revised multi-choice goal programming and its application to renewable energy planning

This paper develops a new goal programming variant, extended revised multi-choice goal programming (ERMCGP), that combines the strengths of revised multi-choice goal programming (RMCGP) and extended goal programming (EGP). In order to achieve this, the revised multi-choice goal programming (RMCGP) variant is first examined from the perspective of modelling the decision maker(s) underlying preferences. The contribution of the RMCGP to the goal programming paradigm and its range of applications are detailed. Five preferential modelling areas for enhancement are then highlighted: (i) algebraic simplification, (ii) separate weighting of deviational variables, (iii) preferential compatibility with one-sided goals, (iv) normalisation and (v) addition of a Chebyshev term to allow balanced solutions. By implementing enhancements (i)-(iv), a modified version of the RMCGP is proposed which is more computationally efficient and preferentially straightforward. Its linkage to a weighted goal programming model with a penalty function is shown. Preferential enhancement (v) leads to the new ERMCGP variant. The modified RMCGP and the ERMCGP are demonstrated using both a small literature example and a newly developed renewable energy allocation example and comparisons are drawn with the original RMCGP and EGP. Conclusions are drawn as to the future development of the ERMCGP within the goal programming framework.