A fuzzy EPQ model with flexibility and reliability consideration and demand dependent unit production cost under a space constraint: A fuzzy geometric programming approach

2006 ◽  
Vol 176 (2) ◽  
pp. 531-544 ◽  
Author(s):  
Sahidul Islam ◽  
Tapan Kumar Roy
2017 ◽  
Vol 8 (2) ◽  
pp. 299
Author(s):  
Sahidul Islam ◽  
Wasim Akram Mandal

In this paper, an Inventory model with unit production cost, time depended holding cost, with-out shortages is formulated and solved. We have considered here a single objective inventory model. In most real world situation, the objective and constraint function of the decision makers are imprecise in nature, hence the coefficients, indices, the objective function and constraint goals are imposed here in fuzzy environment. Geometric programming provides a powerful tool for solving a variety of impreciseoptimization problem. Here we have used nearest interval approximation method to convert a triangular fuzzy number to an interval number then transform this interval number to a parametric interval-valued functional form and solve the parametric problem by geometric programming technique. Here two necessary theorems have been derived. Numerical example is given to illustrate the model through this Parametric Geometric-Programming method. 


2018 ◽  
Vol 24 (4) ◽  
pp. 172-189 ◽  
Author(s):  
Bappa Mondal ◽  
◽  
Arindam Garai ◽  
Tapan Kumar Roy ◽  
◽  
...  

2020 ◽  
Vol 54 (5) ◽  
pp. 1401-1418
Author(s):  
Yasaman Karimian ◽  
Abolfazl Mirzazadeh ◽  
Seyed Hamidreza Pasandideh ◽  
Mohammad Namakshenas

Due to the uncertain situations of the world, considering inventory management in a stochastic environment gains a lot of interest. In this paper, we propose a multi-item economic production quantity (EPQ) model with a shortage for a single-vendor, multi-retailer supply chain under vendor managed inventory (VMI) policy in a stochastic environment. Three stochastic constraints are developed in the model. Geometric programming (GP) approach is employed to find the optimal solution of the nonlinear stochastic programming problem to minimize the mean-variance of the total inventory cost of the system. Since the problem is in the Signomial form, first, an algorithm is used to convert the model into the standard GP form. The performance of the addressed model and the solving method are evaluated based on computational experiments and sensitivity analysis. A case study in an Iranian furniture supply chain is conducted to show the applicability of the proposed model and 17.78% improvement in terms of total cost is gained.


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