Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method

Interval-valued intuitionistic fuzzy multiple attribute decision making based on nonlinear programming methodology and TOPSIS method

Multiattribute group decision making based on intuitionistic fuzzy partitioned Maclaurin symmetric mean operators

A multi-objective supplier selection and order allocation through incremental discount in a fuzzy environment

Due to the fluctuation of market economy and uncertainty of customers' demand, it is quite difficult to develop an appropriate inventory model under uncertain situations. To overcome this difficulty, a food production model with preservation technology and credit‐linked demand under default risk of capital in uncertain environment is developed with the help of parametric approach and interval mathematics. In this proposed model, all the inventory parameters, including demand rate, production rate and deterioration rate are considered as interval‐valued. Because of the consideration of demand rate, production rate as well as deterioration rate as interval‐valued, to represent the proposed model mathematically, the interval differential equations have been used. Solving these differential equations by using parametric approach, all the cost components and the corresponding average profit are obtained in the form of intervals. Therefore, the optimization problem of this model becomes interval‐optimization problem. Then, to solve the interval‐optimization problem, the center‐radius optimization technique is established with the help of interval order relations. With the help of this technique, the interval‐optimization problem is converted into crisp problem and then it is solved numerically by using different variants (Gaussian Quantum‐behaved Particle Swarm Optimization, Weighted Quantum‐behaved Particle Swarm Optimization, and Adaptive Quantum‐behaved Particle Swarm Optimization) of Quantum‐behaved Particle Swarm Optimization technique. Some real‐life problems are considered and solved to justify the validity of the proposed model. The same model is also analyzed in crisp environment to verify the result of interval environment. Finally, the sensitivity analyses of both crisp and interval environments are performed separately with respect to the different system parameters.

An application of interval differential equation on a production inventory model with interval‐valued demand via center‐radius optimization technique and particle swarm optimization

Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment

Fully fuzzy inventory model with price-dependent demand and time varying holding cost under fuzzy decision variables

As a special intuitionistic fuzzy set on a real number set, intuitionistic fuzzy numbers (IFNs) have the best capability to model ill-known quantities. The purpose of this paper is to investigate generalized intuitionistic fuzzy numbers (GIFNs). The weighted possibility, necessity and credibility measures of generalized trapezoidal intuitionistic fuzzy numbers (GTIFN) are introduced, and expected value of GTIFN has been formulated. By employing the possibility and necessity measures of GIFN, the single period multi-product manufacturing generalized intuitionistic fuzzy inventory models is transformed into an equivalent deterministic problem. The transformed problem has been solved by soft computing technique. Finally, the proposed method is illustrated with one numerical example.

Possibility–necessity–credibility measures on generalized intuitionistic fuzzy number and their applications to multi-product manufacturing system

Possibility, necessity, and credibility measures play a significant role to measure the chances of occurrence of fuzzy events. In this paper, possibility, necessity, and credibility measures of exponential fuzzy number, and its expected value has been derived. A multi-item two-warehouse deterministic inventory model for deteriorating items with stock-dependent demand has been developed. For the proposed inventory model, the different costs and other parameters are considered in exponential fuzzy nature. Solution methodology of this model using expected value has been discussed. A numerical example is considered to illustrate the multi-item two-warehouse deterministic inventory model. Finally, few sensitivity analyses are presented under different rates of deterioration to check the validity of the proposed model.

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Expected Value of Exponential Fuzzy Number and Its Application to Multi-item Deterministic Inventory Model for Deteriorating Items

This article focuses on different types of three-layer supply chain models under inflation for non-instantaneous deteriorating item and the retailer has a pre-specified time to settle the account with the supplier. The total cost of each those integrated models under inflation is minimized to get the value of total cycle time and the credit period of the three-layer supply chain model. A numerical example is extracted to solve the proposed three-layer supply chain models using generalized reduced gradient technique. To test the feasibility of the proposed models, sensitivity analyses are explained under different rates of deterioration and inflation and then optimal results are illustrated numerically and graphically.

Totan Garai

Papers

Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment

Fully fuzzy inventory model with price-dependent demand and time varying holding cost under fuzzy decision variables

Possibility–necessity–credibility measures on generalized intuitionistic fuzzy number and their applications to multi-product manufacturing system

Expected Value of Exponential Fuzzy Number and Its Application to Multi-item Deterministic Inventory Model for Deteriorating Items

A three-layer supply chain inventory model for non-instantaneous deteriorating item with inflation and delay in payments in random fuzzy environment