International journal of fuzzy logic and intelligent systems/International Journal of Fuzzy Logic and Intelligent System, Mar 31, 2024
Supplier selection is an important aspect of effective supply chain management (SCM) and has impl... more Supplier selection is an important aspect of effective supply chain management (SCM) and has implications in risk mitigation, profitability, and cultivating robust supplier-buyer relationships. In this dynamic and competitive landscape, it is essential to implement multi-criteria decisionmaking (MCDM) methods. Therefore, we employ the technique for order performance by similarity to ideal solution (TOPSIS), an MCDM technique, to evaluate the best supplier. Our approach incorporates fuzzy intuitionistic data and leverages the insights of decision-makers. Seven essential criteria, namely, supplier relationships, patient demand, quality, profitability, delivery time, post-delivery service, and patient cost, are integral to this assessment. This methodology is particularly valuable in situations that require swift supplier selection and those that cater to the urgent supplier needs of pharmacists. While our focus was on a specific context, the adaptability of this approach enables researchers to customize it for their respective fields by incorporating pertinent criteria based on expert inputs. Supplier evaluation within the healthcare sector, focusing on sector-specific metrics such as antibiotic drug selection, remains a relatively unexplored area. To address this issue, we present a comprehensive framework to select antibiotic drug suppliers.
A multi item profit maximization inventory model is developed in fuzzy stochastic environment. De... more A multi item profit maximization inventory model is developed in fuzzy stochastic environment. Demand is taken as Stock dependent demand. Available storage space is assumed to be imprecise and vague in nature. Impreciseness has been expressed by linear membership function. Purchasing cost and investment constraint are considered to be random and their randomness is expressed by normal distribution. The model has been formulated as a fuzzy stochastic programming problem and reduced to corresponding equivalent fuzzy linear programming problem. The model has been solved by using fuzzy linear programming technique and illustrated numerically.
A Nonlinear Programming Approach to Solve the Stochastic Multi-objective Inventory Model Using the Uncertain Information
Arabian Journal for Science and Engineering, 2020
A multi-objective, multi-item fuzzy stochastic inventory model is constructed for deteriorating i... more A multi-objective, multi-item fuzzy stochastic inventory model is constructed for deteriorating items under limited storage space as well as capital investment. Demand is considered as a function of price and frequency of advertisements. In this model, some parameters are considered to be vague and some are random. The vagueness of parameters is represented by membership function, and randomness of parameters is represented by a probability distribution. In the inventory model, if some parameters are vague and some are probabilistic, then the model is called a fuzzy stochastic model. Here, parameters such as purchasing cost, shortage costs as well as a capital investment are considered to be random in nature and storage space is considered as imprecise. The randomness of a parameter is represented by a normal distribution, and the impreciseness of parameters is expressed using linear membership function. By using fuzzy nonlinear programming (FNLP) and intuitionistic fuzzy optimization (IFO) techniques, a solution for the multi-objective fuzzy stochastic inventory model is obtained. The major goal of the paper is to find an optimal quantity to be replenished. The objective of this work is to study the effect of capital investment and warehouse space on profit as well as shortage cost through sensitivity analysis. The other objective is to compare the efficiency of FNLP and IFO techniques for obtaining solutions through numerical results. This paper shows that FNLP works better than IFO in case of minimizing shortage cost.
International Journal of Procurement Management, 2018
In this paper multi-item fuzzy profit maximisation inventory model with ramp type demand under im... more In this paper multi-item fuzzy profit maximisation inventory model with ramp type demand under imprecise space, budget constraints and imprecise holding cost with two storage facilities are presented. There are two warehouses, one is situated at market place called as own warehouse (OW) and another is little away from market place called as rented warehouse (RW). The sale is conducted from OW and the sold items are replaced continuously by the items at RW. Here shortages are not allowed. The fuzzy model has been solved by using fuzzy nonlinear programming technique and illustrated numerically.
Optimizing of Multi-objective Inventory Model by Different Fuzzy Techniques
International Journal of Applied and Computational Mathematics, 2019
A multi-objective, multi item inventory model is constructed for deteriorating items where the de... more A multi-objective, multi item inventory model is constructed for deteriorating items where the demand is considered as exponential time function under limited storage space as well as budget. By using Fuzzy non linear programming (FNLP) and Intutionistic fuzz optimization (IFO) techniques results are obtained and then compared. The objective of this work is to use FNLP and IFO techniques for multi-objective inventory model and to compare these techniques through numerical results. The major goal of the paper is to find optimal quantity to be replenished and identify time point when shortages will occur. In this paper FNLP and IFO are applied to multi item multi-objective inventory model with budget and warehouse space constraint and investigating for multi-objective inventory model which method either FNLP or IFO gives efficient solution. In case of maximization objective IFO works well than FNLP while in case of minimization FNLP works better. By observing objectives, the above methods can apply to various inventory problems. All these results along with relation of profit and shortage cost with budget, warehouse space is studied through sensitivity analysis. The result shows that the IFO better results for maximizing profit while FNLP works better in case of minimizing shortage cost.
A multi item profit maximization inventory model is developed in fuzzy stochastic environment. De... more A multi item profit maximization inventory model is developed in fuzzy stochastic environment. Demand is taken as Stock dependent demand. Available storage space is assumed to be imprecise and vague in nature. Impreciseness has been expressed by linear membership function. Purchasing cost and investment constraint are considered to be random and their randomness is expressed by normal distribution. The model has been formulated as a fuzzy stochastic programming problem and reduced to corresponding equivalent fuzzy linear programming problem. The model has been solved by using fuzzy linear programming technique and illustrated numerically.
American Journal of Applied Mathematics and Statistics, 2014
In this Paper a multi item EOQ model with stock dependent demand for deteriorating items is consi... more In this Paper a multi item EOQ model with stock dependent demand for deteriorating items is considered in fuzzy environment. Inventory costs such as holding cost and setup cost have been represented by exponential membership function and profit, deteriorating rate and total investment constraint are represented by linear membership functions. The model has been solved by fuzzy non-linear programming (FNLP) method. Results have been presented along with those of corresponding crisp model and a sensitivity analysis.
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Papers by Hemant Umap