عنوان مقاله
یک روش تخصیص منابع بر پایه مدل هایDEA و تحلیل های کشش
فهرست مطالب
مقدمه
پس زمینه
یک روش تخصیص منابع جدید
مثال عددی
نتیجه گیری
بخشی از مقاله
پس زمینه
یک کارخانه دارای 15 دپارتمان می باشد : A ، B ، ..... و D این دپارتمان ها نوع یکسان ولی مقدار متفاوت از مواد خام را برای تولید محصول استفاده می کنند. در اینجا ورودی مقدار مواد خامی که هر دپارتمان استفاده کرده است ( هر 100 کیلوگرم یک واحد) و خروجی تعداد محصولی که هر دپارتمان تولید کرده است را نشان می دهد ( هر 100 عدد یک واحد). اگر کارخانه 100000 کیلوگرم مواد خام اضافی بخرد چگونه باید تصمیم گیرنده آن را به 15 دپارتمان تخصیص دهد؟ این مساله با 15Dmu یک مسئله تک ورودی و تک خروجی می باشد .
کلمات کلیدی:
A Resource Allocation Mode Based on DEA Models and Elasticity Analysis∗ Qia Wang Jin-Chuan Cui Institute of Applied Mathematics Academy of Mathematics and Systems Science, CAS, Beijing 100190 Abstract This paper proposes a new resource allocation mode based on DEA models and elasticity analysis for a certain kind of resource allocation problems. It takes into account both the relative efficiency and the returns-to-scale of the decision making units. The decision maker can adopt it to comprehensively evaluate the departments’ production capacity and their potential production capacity. At last, this paper applies this mode into the single input and single output case. The results show that it can reflect the returns-to-scale more precisely than before. Keywords Data Envelopment Analysis (DEA); resource allocation problem; returns-to-scale; elasticity 1 Introduction The resource allocation problem has a great practical applied value. The difficulty of this problem is: how to evaluate the departments involved in the allocation, and how to determine their allocation weights. Recently, using DEA models to solve this problem has become a new research area. That is because DEA is a synthetic method measuring the relative efficiency of homogeneous production departments (referred to as decision making units, DMU) (see [1][4][5]). Moreover, the inputs and outputs weights vector obtained by DEA models is the Pareto solution for multiobjective programming, and it satisfies the Nash equilibrium condition as well(see [7]). In paper [8] and [9], they clearly define the extra resource allocation problem, and propose that the decision maker should take into account both the efficiency and the scale. Subsequently, paper [2] and [3] suggest the decision maker should consider the returns-to-scale also when dealing with this problem. Returns-to-scale (RTS) is a concept in economics, which reflects the potential production capacity when inputs are increased (see [4][5]). It has 4 types: the increase returns-to-scale (IRS), the constant returns-to-scale (CRS), the decrease returns-to-scale (DRS), and the Congestion. Thus the previous way of solving the resource allocation problem is: calculate the efficiency and the type of returns-to-scale from the DEA models for each DMU, then figure out all DMUs’ allocation weights. However, this resource allocation mode based on the 4 types of RTS has some shortcomings, which will be illustrated.
