Fairness Measures for Resource Allocation

In many optimization problems, one seeks to allocate a limited set of resources to a set of individuals with demands. Thus, such allocations can naturally be viewed as vectors, with one coordinate representing each individual. Motivated by work in network routing and bandwidth assignment, we consider the problem of producing solutions that simultaneously approximate all feasible allocations in a coordinate-wise sense. This is a very strong type of "global" approximation guarantee, and we explore its consequences in a range of discrete optimization problems, including facility location, scheduling, and bandwidth assignment in networks. A fundamental issue-one not encountered in the traditional design of approximation algorithms-is that good approximations in this global sense need not exist for every problem instance; there is no a priori reason why there should be an allocation that simultaneously approximates all others. As a result, the existential questions concerning such good allocations lead to a new perspective on a number of basic problems in resource allocation, and on the structure of their feasible solutions.

Authors

• Amit Kumar 0001
• Jon M. Kleinberg

Keywords

• Resource management
• Bandwidth
• Computer science
• Routing
• Algorithm design and analysis
• Aggregates
• Career development
• Channel allocation
• Good Approximation
• Feasible Solution
• Range Of Problems
• Local Facilities
• Problem Instances
• Network Routing
• Completion Time
• Types Of Problems
• Time Slot
• Sum Rate
• Polynomial-time Algorithm
• Partial Order
• Release Date
• Nearest Facility
• Distance Vector
• Single Edge
• Makespan
• Online Algorithm
• Time Vector
• Identical Machines
• Bandwidth Allocation
• Precedence Constraints
• Demand Points
• Facility Location Problem
• Precedence Relations
• Parallel Machines
• Job Completion Time
• Lexicographic