scholarly journals A Scenario-based Model for Resource Allocation with Price Information

2021 ◽  
Vol 46 (4) ◽  
pp. 339-360
Author(s):  
Mojtaba Ghiyasi ◽  
Akram Dehnokhalaji
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Linear Programming ◽  
Cost Efficiency ◽  
Price Information ◽  
Linear Programming Problems ◽  
Overall Efficiency ◽  
Decision Making Units

Abstract In this paper, we consider the problem of allocating resources among Decision Making Units (DMUs). Regarding the concept of overall (cost) efficiency, we consider three different scenarios and formulate three Resource Allocation (RA) models correspondingly. In the first scenario, we assume that overall efficiency of each unit remains unchanged. The second scenario is related to the case where none of overall efficiency scores is deteriorated. We improve the overall efficiencies by a pre-determined percentage in the last scenario. We formulate Linear Programming problems to allocate resources in all scenarios. All three scenarios are illustrated through numerical and empirical examples.

scholarly journals New Approach in Fixed Resource Allocation and Target Setting Using Data Envelopment Analysis with Common Set of Weights

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Marzieh Ghasemi ◽  
Mohammad Reza Mozaffari ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy malkhalifeh ◽  
Mohammad Hasan Behzadi
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Target Setting ◽  
New Approach ◽  
Common Set Of Weights ◽  
Programming Techniques ◽  
Using Data ◽  
Decision Making Units

One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights (CSW). All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example.

RANKING THE EFFICIENCY PERFORMANCE WITHIN A SET OF DECISION MAKING UNITS BY DATA ENVELOPMENT ANALYSIS

2005 ◽  
Vol 04 (03) ◽  
pp. 345-357 ◽  
Author(s):  
HONGYU LI ◽  
JISHAN ZHU
Keyword(s):  
Linear Programming ◽  
Regression Function ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Data Set ◽  
Efficiency Performance ◽  
Dea Efficiency ◽  
Linear Programming Problems ◽  
Overall Efficiency ◽  
Single Regression

In contrast to parametric approaches which try to optimize a single regression function through the observed data set, DEA optimizes on each individual observation with a objective of calculating a discrete piece-wise linear frontier. In the so-called preliminary DEA efficiency evaluation, whether or not a DMU is efficient is solely determined by the solution of the linear programming problem constructed for this particular DMU. In our proposed ranking method, we assess the efficiency performance of a particular DMU based not only on its efficiency score when the DMU is standing out in the objective function of the linear problem but also its efficiency ratios under the optimal solutions of other n-1 linear programming problems. This constitutes the overall efficiency performance of a DMU. A ranking procedure is developed to rank the n DMUs in terms of the overall efficiency performance.

MODELING OUTPUT GAINS AND EARNINGS' GAINS

2005 ◽  
Vol 04 (03) ◽  
pp. 433-454 ◽  
Author(s):  
HIROFUMI FUKUYAMA ◽  
WILLIAM L. WEBER
Keyword(s):  
Decision Making ◽  
Cost Efficiency ◽  
Costs Of Production ◽  
Using Data ◽  
Input Prices ◽  
Decision Making Units ◽  
Empirical Illustration

In this paper, we examine the potential gains in physical outputs or earnings on outputs from an optimal reallocation of inputs. When some decision-making units (DMUs) face higher input prices than other DMUs, the Farrell decomposition of cost efficiency can potentially indicate that a firm with lower overall costs of production is less efficient than a firm that uses fewer physical inputs, but has higher costs. We extend our gain functions accounting for cases where DMUs face different input prices. An empirical illustration of our method is provided using data on Japanese banks operating during 2000–2003.

DETERMINATION OF SOLVABILITY BOUNDARIES OF OPTIMIZATION PROBLEMS IN PARAMETER SPACE

1993 ◽  
Vol 03 (04) ◽  
pp. 453-462
Author(s):  
A.P. CHERENKOV ◽  
V.V. MIKHAILENKO ◽  
B.S. SHUSTERMAN
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Linear Programming ◽  
Dynamic Model ◽  
Parameter Space ◽  
Optimization Problems ◽  
Monotone Function ◽  
Complex Program ◽  
Parameter Values

This paper is devoted to the determination of parameter values of optimization problems for which they are solvable. In relation to this, the concept of monotone solvability with respect to parameter is essentially used. The procedure of construction of solvability boundaries in parameter space is realized, and it is essentially reduced to decipher the monotone function. This procedure is used for the consideration of a dynamic model of simulative control of the geological-prospecting process (the resource allocation between stages of geological-prospecting work). On the basis of this procedure using the standard package of linear programming, the complex program of decision-making for personal computers compatible with IBM XT/AT is implemented.

Sign in / Sign up

Export Citation Format

Share Document