Fair resource allocation: Using welfare-based dominance constraints

被引:27
作者
Argyris, Nikolaos [1 ]
Karsu, Ozlem [2 ]
Yavuz, Mirel [3 ]
机构
[1] Loughborough Univ, Sch Business & Econ, Loughborough, Leics, England
[2] Bilkent Univ, Dept Ind Engn, Ankara, Turkey
[3] Univ Calif Los Angeles, Anderson Sch Management, Box 951481, Los Angeles, CA 90095 USA
关键词
Decision support systems; Resource allocation; Fairness; Efficiency; Social welfare; LOCATION; EQUITY; OPTIMIZATION; EFFICIENCY; DISPERSION; RANKING;
D O I
10.1016/j.ejor.2021.05.003
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In this paper we consider the problem of supporting resource allocation decisions affecting multiple beneficiaries. Such problems inherently involve efficiency-fairness trade-offs. We introduce a new approach based on the paradigm of maximizing efficiency subject to constraints to ensure that the decision is acceptably fair. In contrast to existing literature, we incorporate fairness in the form of welfare dominance, ensuring that the resultant distribution of benefits to beneficiaries is at least as good as some reference distribution with respect to a set of social welfare functions that satisfy commonly accepted efficiency and fairness related axioms. We introduce a practical means to parameterize the problem, which allows for excluding welfare functions that are deemed insufficiently or overly sensitive to inequality. This allows for analyzing the impact of changes in inequality aversion on efficiency, thus revealing the trade-off between efficiency and fairness. We develop tractable reformulations for the resulting non-linear multilevel optimization problems. We then extend this approach for cases where resources are allocated to groups of individuals with different sizes. We demonstrate the potential use of the suggested framework on two case studies: a workload allocation problem and a healthcare provisioning problem. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:560 / 578
页数:19
相关论文
共 49 条
[1]   Mathematical programming models and algorithms for a class-faculty assignment problem [J].
Al-Yakoob, Salem M. ;
Sherali, Hanif D. .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 173 (02) :488-507
[2]   A review of interactive methods for multiobjective integer and mixed-integer programming [J].
Alves, Maria Joao ;
Climaco, Joao .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 180 (01) :99-115
[3]  
[Anonymous], 2016, MULTIPLE CRITERIA DE, DOI [10.1007/978-1-4939-3094-4_22, DOI 10.1007/978-1-4939-3094-4_22, DOI 10.1007/978-1-4939-3094-422]
[4]   Decision Making Under Uncertainty When Preference Information Is Incomplete [J].
Armbruster, Benjamin ;
Delage, Erick .
MANAGEMENT SCIENCE, 2015, 61 (01) :111-128
[5]   Advancing equitability in multiobjective programming [J].
Baatar, D. ;
Wiecek, M. M. .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2006, 52 (1-2) :225-234
[6]   The equitable location problem on the plane [J].
Baron, Opher ;
Berman, Oded ;
Krass, Dmitry ;
Wang, Qlan .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 183 (02) :578-590
[7]   Public facility location using dispersion, population, and equity criteria [J].
Batta, Rajan ;
Lejeune, Miguel ;
Prasad, Srinivas .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2014, 234 (03) :819-829
[8]  
BENPORATH E, 1994, J ECON THEORY, V64, P443
[9]   Dynamic resource allocation: A flexible and tractable modeling framework [J].
Bertsimas, Dimitris ;
Gupta, Shubham ;
Lulli, Guglielmo .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2014, 236 (01) :14-26
[10]   On the Efficiency-Fairness Trade-off [J].
Bertsimas, Dimitris ;
Farias, Vivek F. ;
Trichakis, Nikolaos .
MANAGEMENT SCIENCE, 2012, 58 (12) :2234-2250