On Equitable Resource Allocation Problems: A Lexicographic Minimax Approach

Hanan Luss
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Hanan Luss: Telcordia Technologies (formerly Bellcore), Piscataway, New Jersey

Operations Research, 1999, vol. 47, issue 3, 361-378

Abstract: In this expository paper, we review a variety of resource allocation problems in which it is desirable to allocate limited resources equitably among competing activities. Applications for such problems are found in diverse areas, including distribution planning, production planning and scheduling, and emergency services location. Each activity is associated with a performance function, representing, for example, the weighted shortfall of the selected activity level from a specified target. A resource allocation solution is called equitable if no performance function value can be improved without either violating a constraint or degrading an already equal or worse-off (i.e., larger) performance function value that is associated with a different activity. A lexicographic minimax solution determines this equitable solution; that is, it determines the lexicographically smallest vector whose elements, the performance function values, are sorted in nonincreasing order. The problems reviewed include large-scale allocation problems with multiple knapsack resource constraints, multiperiod allocation problems for storable resources, and problems with substitutable resources. The solution of large-scale problems necessitates the design of efficient algorithms that take advantage of special mathematical structures. Indeed, efficient algorithms for many models will be described. We expect that this paper will help practitioners to formulate and solve diverse resource allocation problems, and motivate researchers to explore new models and algorithmic approaches.

Keywords: programming; large-scale systems; resource allocation algorithms; programming; multiple criteria; lexicographic minimax objective; production/scheduling; applications; resource allocation models (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (46)

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