Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions

Amin Hocine, Zheng Yun Zhuang, Noureddine Kouaissah, Der Chiang Li

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


This paper proposes a novel weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) model for the imprecise decision context wherein several conflicting goals are present but each goal has multiple-choice aspiration levels (MCALs) and, around them, the fuzzinesses are expressed in terms of membership functions (MFs). The main contribution of this model is its use of an objective function that minimises the weighted-additive summation of the normalised deviations; thus, the model can adopt any minimisation process from any goal programming (GP) variant. The advantages of this FGP-MCGP (fuzzy GP – multi-choice GP) model are shown by using it to solve a numerical example from F-MODM (fuzzy MODM) literature and comparing the results with those of a recent FP-MCGP (fuzzy programming – multi-choice GP) study. The application of the model is also verified using real data (i.e., it can model and support renewable energy site selection (RESS) where the decision context is imprecise). As WA-FMCGP is largely a MODM model, through its application, this study also provides a supplementary method in contrast to the multi-attribute decision-making (MADM) model applications used thus far for RESS.

Original languageEnglish
Pages (from-to)642-654
Number of pages13
JournalEuropean Journal of Operational Research
Issue number2
Publication statusPublished - 2020 Sep 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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