Selecting a Project Delivery System for Wastewater Treatment Plants With Related-Indicators Under a Pythagorean Fuzzy Environment

A NEW MULTI-OBJECTIVE OPTIMIZATION APPROACH FOR SUSTAINABLE PROJECT PORTFOLIO SELECTION: A REALWORLD APPLICATION UNDER INTERVAL-VALUED FUZZY ENVIRONMENT

Organizations need to evaluate project proposals and select the ones that are the most effective in reaching the strategic goals by considering sustainability issue. In order to enhance the effectiveness and the efficiency of project oriented organizations, in this paper a new multi-objective decision making (MODM) approach of sustainable project portfolio selection is proposed which applies in...

Extensions of ELECTRE-I and TOPSIS methods for group decision-making under complex Pythagorean fuzzy environment

Multi-criteria group decision-making is a process in which decision makers assess the performance of alternatives on the basis of conflicting criteria to opt the most worthy alternative as solution. TOPSIS and ELECTRE are effective and commonly used methods to solve multiple criteria decision-making problems. The aim of this study is to propose two new models, namely, complex Pythagorean fuzzy ...

A Model for Project Selecting with Limited Resources in Data Envelopment Analysis with Input and Output Fuzzy

In Evaluating Performance, Selecting a Subset from a Set of Solutions with Limited Resources is Essential. If There Is More Than One Input and Output, the Data Rnvelopment Analysis Optimization Models Are Evaluated and Performance Measurement Based on the Weighted Output Is Divided Weighted Input. In This Research, Two Models of Optimization with Limited Resources Present from Data Envelopment ...

Fuzzy Design of Wastewater Treatment Plants

A Multi-Criteria Analysis Model under an Interval Type-2 Fuzzy Environment with an Application to Production Project Decision Problems

Using Multi-Criteria Decision-Making (MCDM) to solve complicated decisions often includes uncertainty, which could be tackled by utilizing the fuzzy sets theory. Type-2 fuzzy sets consider more uncertainty than type-1 fuzzy sets. These fuzzy sets provide more degrees of freedom to illustrate the uncertainty and fuzziness in real-world production projects. In this paper, a new multi-criteria ana...