No abstract

In this study, multi-objective inventory model of deteriorating and perishable items is developed under space and budget constraints. Demand is stock dependent and power function of time. This model is completely a new model in the sense that the model is applied to those items whose deterioration rate is maximum. Shortages are allowed in each cycle. The main aim of this paper is to find different time points for each cycle where shortage occurs and inventory depletes respectively so that both total cost and shortage cost can be minimized simultaneously. The model is developed in both crisp and fuzzy environment. In fuzzy environment, the objectives are considered as fuzzy constraints. For this the decision maker needs to establish an aspiration level for the objective functions which he wants to achieve as far as possible. This paper aims to use fuzzy non-linear programming (FNLP) and intuitionistic fuzzy optimization (IFO) techniques for the multi-objective inventory model. Comparison is based on different optimization techniques in different environment using numerical examples. Graph of the objective functions are provided. System diagram of the model and algorithm for solving the model are provided. Also, sensitivity analysis is made using different parameters of the model.

A single-item deterministic inventory model for deteriorating items with fuzzy demand under a finite time horizon have been developed. Here, shortage has occurred only at a particular time period. Using Signed distance method, the fuzzy objective function is converted into crisp equivalent form. Both in crisp and fuzzy environment, numerical examples are provided. The objective function which is to be optimized by the number of replenishment is calculated using the calculus method. Finally, we find the values in the fuzzy environment which is to be corrected for optimal solution.

In this study, multi-objective inventory model of deteriorating and perishable items is developed under space and budget constraints. Demand is stock dependent and power function of time. This model is completely a new model in the sense that the model is applied to those items whose deterioration rate is maximum. Shortages are allowed in each cycle. The main aim of this paper is to find different time points for each cycle where shortage occurs and inventory depletes respectively so that both total cost and shortage cost can be minimized simultaneously. The model is developed in both crisp and fuzzy environment. In fuzzy environment, the objectives are considered as fuzzy constraints. For this the decision maker needs to establish an aspiration level for the objective functions which he wants to achieve as far as possible. This paper aims to use fuzzy non-linear programming (FNLP) and intuitionistic fuzzy optimization (IFO) techniques for the multi-objective inventory model. Comparison is based on different optimization techniques in different environment using numerical examples. Graph of the objective functions are provided. System diagram of the model and algorithm for solving the model are provided. Also, sensitivity analysis is made using different parameters of the model.

In this study, multi-objective inventory model of deteriorating and perishable items is developed under space and budget constraints. Demand is stock dependent and power function of time. This model is completely a new model in the sense that the model is applied to those items whose deterioration rate is maximum. Shortages are allowed in each cycle. The main aim of this paper is to find different time points for each cycle where shortage occurs and inventory depletes respectively so that both total cost and shortage cost can be minimized simultaneously. The model is developed in both crisp and fuzzy environment. In fuzzy environment, the objectives are considered as fuzzy constraints. For this the decision maker needs to establish an aspiration level for the objective functions which he wants to achieve as far as possible. This paper aims to use fuzzy non-linear programming (FNLP) and intuitionistic fuzzy optimization (IFO) techniques for the multi-objective inventory model. Comparison is based on different optimization techniques in different environment using numerical examples. Graph of the objective functions are provided. System diagram of the model and algorithm for solving the model are provided. Also, sensitivity analysis is made using different parameters of the model.