An effective solution approach for multi-objective optimization problems in a Hesitant intuitionistic fuzzy environment

Decision-making is an inevitably complex task we face in our daily lives in the modern world. Accordingly, many practical problems have become increasingly sophisticated due to uncertainties, vagueness, and incomplete information, as well as the hesitancy and subjective nature of Decision-Makers (DMs), leading scholars to propose various solution methods. However, for the problems in the Hesitant Intuitionistic Fuzzy Environment (HIFE), their methods are mainly devoted to Multi-Criteria Decision-Making (MCDM) problems. There are a few studies which considered Hesitant Intuitionistic Fuzzy Optimization (HIFO) approaches to Multi-Objective Optimization (MOO) problems. Nevertheless, when addressing problems involving multiple DMs, these methods have not thoroughly considered all possible degrees of acceptance and rejection alternatives into the solving procedures. Thus, the main objective of this study is to propose an effective solution method for MOO problems in HIFE. For this purpose, the aggregation operators for MCDM problems are adapted to MOO problems. We have proved the satisfaction of Pareto Optimality Conditions (POC) of the solution obtained by using the proposed method. We have established the advantages and effectiveness of the proposed method over the existing approach using illustrative examples and a practical case study in Agricultural Crop Production Planning (ACPP) problems.

کلیدواژه ها:

Multi-objective optimization problem ، Hesitant intuitionistic fuzzy optimization ، Hesitant intuitionistic fuzzy aggregation operator ، Decision-making ، Agricultural crop production planning