Optimization of unconstrained multi-item (EPQ) model using fuzzy geometric programming with varying fuzzification and defuzzification methods by applying python

Author(s):  
K. Kalaiarasi ◽  
M. Sabina Begum ◽  
M. Sumathi
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.


2017 ◽  
Vol E100.C (4) ◽  
pp. 407-415
Author(s):  
Minyoung YOON ◽  
Byungjoon KIM ◽  
Jintae KIM ◽  
Sangwook NAM

2013 ◽  
Vol 5 (3) ◽  
pp. 373-380
Author(s):  
Zeinab Kheiri ◽  
Faezeh Zahmatkesh ◽  
Bing-Yuan Cao

1980 ◽  
Vol 102 (3) ◽  
pp. 154-159 ◽  
Author(s):  
A. Lavi

A complex power system may be modeled by a system of inequalities representing the constraints imposed by the physical laws: heat transfer, energy balance, cycle efficiency and so forth. The nature of the resulting mathematical model is such that the terms contain complex expressions involving the design and operating variables of the process. With the addition of an objective function involving the cost of major system components, a multivariable nonlinear programming problem can be formulated. Seldom does the model lend itself to analytical treatment. This paper is concerned with a specific formulation and solution of nonlinear programming problems which arise in the design of ocean thermal energy conversion (OTEC) power plants. The technique used is geometric programming, GP. It is shown that GP serves as an excellent tool for system analysis because it provides sensitivity information essential to the designer.


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