In recent years, taking advantage of LARG supply chain (SC) paradigm, a combination of four paradigms (clean, agile, resilience and green) has been increasingly employed. For capturing the advantages of LARG in SC, companies needed to recognize proper practices and implement them with appropriate planning and infrastructure. However, one of its deficiencies is lack of proper method in the prior...

Species selection based on a new method such as a fuzzy method is one of the most important stages in the successful plantation management planning as choosing a suitable species for the site can be the key to success. This paper is based on a fuzzy extension of the Technique or Order Preference which is similar to Ideal Solution (TOPSIS) method. The purpose of this paper is to develop fuzzy TO...

Trapezoidal intuitionistic fuzzy numbers (TrIFNs) express abundant and flexible information in a suitable manner and  are very useful to depict the decision information in the procedure of decision making. In this paper, some new aggregation operators, such as, trapezoidal intuitionistic fuzzy weighted power harmonic mean (TrIFWPHM) operator, trapezoidal intuitionistic fuzzy ordered weighted po...

In this paper, a hybrid multi-criteria decision-making (MCDM)-method and mixed integer linear programming (MILP) approach in order to evaluation of the returned products' collectors along with their ordered quantities, is utilized. Firstly, the most important criteria of collection center in the car industry are identified. Then, in order to evaluate these proposed criteria, a hybrid Fuzzy Deci...

Selecting the most suitable alternative under uncertainty is considered as a critical decision-making problem that affects the success of organizations. In the selection process, there are a number of assessment criteria, considered by a group of decision makers, which often could be established in a multi-level hierarchy structure. The aim of this paper is to introduce a new hierarchical multi...

in this paper, we show that inverse data envelopment analysis (dea) models can be used to estimate output with fuzzy data for a decision making unit (dmu) when some or all inputs are increased and deficiency level of the unit remains unchanged.