Influence of fuzzy Goal Programming in Production Optimization Case study: Cement Industry

Subject Areas : طراحی آزمایشات

Mahmoud  Modiri ¹ (Islamic Azad University, Tehran South Branch, Department of management, Tehran, Iran)
Saeid  Moheb Rabbani ² (Islamic Azad University, Qazvin Branch, Department of management and Accounting, Qazvin, Iran)
Hadi  Heidari Gharebolagh ³ (Islamic Azad University, Qazvin Branch, Department of management and Accounting, Qazvin, Iran)

Received: 2010-07-23 Accepted : 2010-08-06 Published : 2010-09-28

Keywords: Fuzzy linear programming, Analytical Hierarchy Process (AHP), Fuzzy Goal Programming,

Abstract :

Using the mathematic techniques such as Fuzzy approach has useful outcomes for production planning in different sources. In this paper LGP1 was used to model the objectives such as: avoidance of shortage or surplus of demand, access to maximum of income, using the normal capacity of production and organizing the inventory of warehouse, within the framework of Goal constraints like balancing between demand and inventory, rate of production within every period and the constraints of threshold of inventory at the end of every month. On these lines, the goal programming is one of the best methods for analyzing the multi objective decision making in cement industry management. The most principal disadvantage of goal programming is that all the parameters of model should be defined carefully and all of the objectives and constraints should certainly be determined. For taking over on this problem we introduced the Fuzzy concept. In this research, the mathematic goal programming model in the cement industry is modeled by Fuzzy and absolute approach. This research is intended to answer this question, which one presents the optimal solution for production process planning, Fuzzy or absolute approach? The necessity information to do this research is obtained with using field methods, desk surveys, observations, factory documents, and interviews or questionnaires. In this article we use GP to formulize, AHP2 for grading and weighting and LINGO for solving. Afterwards, the data are entered in the formula modeled before and are solved using LINGO software.