@article{Saracoglu_Mahallesi_Caddesi_Sokak_2015, title={A COMPARATIVE STUDY OF AHP, ELECTRE III & ELECTRE IV BY EQUAL OBJECTIVE & SHANNON’S ENTROPY OBJECTIVE & SAATY’S SUBJECTIVE CRITERIA WEIGHTING IN A PRIVATE SMALL HYDROPOWER PLANTS INVESTMENTS SELECTION PROBLEM}, volume={7}, url={https://www.ijahp.org/index.php/IJAHP/article/view/343}, DOI={10.13033/ijahp.v7i3.343}, abstractNote={<p>Private small hydropower plant investments are more challenging than medium and large private hydropower plant investments when considering engineering analysis. One of the necessary tasks is the selection of the most appropriate private small hydropower investment amongst several alternatives. Brokerage, consultancy and private investor activities are a few examples of these kinds of real world activities. There are many multi-criteria decision making (MCDM) or multiple-criteria decision analysis (MCDA) methods, and different researchers prefer different methods This research study investigates three methods at once for the same problem: Analytic Hierarchy Process (AHP), Elimination and Choice Translating Reality (ELECTRE) III and ELECTRE IV. A comparative investigation is conducted on one simple unique selection model for all three methods. This unified model has seven objective factors (catchment area, project runoff, net head, flow rate, firm energy, secondary energy, investment cost). An additional comparison is also made on the criteria weighting amongst equal objective, Shannon’s Entropy objective and Saaty’s subjective criteria weighting. The simplistic unified model is structured in three levels. There are seven alternatives in the pre-development investment stage. The Super Decisions software and the ELECTRE III-IV software are implemented in this study. The pairwise comparisons of factors results in an inconsistency value of 0,09511 which is 7<sup>th</sup> in the Saaty’s AHP weighting. The Shannon’s Entropy objective weighting represents a difference in the rate of the expert decision maker’s evaluations ranging between -67% and 671%. The equal weighting represents a rate change between -64% and 626%. Both approaches can’t represent human judgments (here only one expert decision maker) well in this model. Fortunately, the same alternative (Alternative 3) ranks first. These findings promise that further studies on this subject can give some clues for the development of an autonomous computer based intelligent decision support system. Some observed pros and cons of these methods are also presented in this study. The observations and critical issues are presented during modeling, application, evaluation and analysis to help researchers, consultants, and readers in the small hydropower investments research and practical fields.  </p>}, number={3}, journal={International Journal of the Analytic Hierarchy Process}, author={Saracoglu, Burak Omer and Mahallesi, Orhantepe and Caddesi, Tekel and Sokak, Geziyolu}, year={2015}, month={Dec.} }