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Mathematical Problems in Engineering
Volume 2018 (2018), Article ID 3826096, 10 pages
https://doi.org/10.1155/2018/3826096
Research Article

Centralized Resource Allocation and Target Setting Based on Data Envelopment Analysis Model

1Department of Philosophy of Science, University of Science and Technology of China, Hefei, Anhui Province 230026, China
2School of Management, University of Science and Technology of China, Hefei, Anhui Province 230026, China
3School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China

Correspondence should be addressed to Feng Li

Received 17 August 2017; Accepted 31 December 2017; Published 5 February 2018

Academic Editor: Josefa Mula

Copyright © 2018 Tiantan Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper aims to develop a data envelopment analysis (DEA) based model for allocating input resources and deciding output targets in organizations with a centralized decision-making environment, for example, banks, police stations, and supermarket chains. The central decision-maker has an interest in maximizing the total output production and at the same time minimizing the total input consumption. Traditionally, all decision-making units (DMUs) can be easily projected to the efficient frontier, which is a mathematical feasibility; however, it does not guarantee the managerial feasibility during the planning period. In this paper, we will take potential limitations of input-output changes into account by building a difficulty coefficient matrix of modifying their production in the current production possibility set so that the solution guarantees managerial feasibilities. Three objectives, namely, maximizing aggregated outputs, minimizing the consumption of input resources, and minimizing the total difficulty coefficient, are proposed and incorporated into the formation of resource allocation and target setting scheme. Building on this, we combine DEA and multiobjective programming to solve the resource allocation and target setting problem. In the end, we apply our proposed approach to a real-world problem of sixteen chain hotels to illustrate the efficacy and usefulness of the proposed approach.