A genetic algorithm approach to the selection of near-optimal subsets from large sets

  • Authors:

  • P. Whiting;P. W. Poon;J. N. Carter

  • Affiliations:

  • Tillinghast, London, UK;Tillinghast, London, UK;Imperial College, London, UK

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an optimisation problem where one selects a subset of r objects from a group of n objects and the objective function is the mismatch between the required average property and that of a proposed sample. We test our method on a real-life problem which arises when we model the assets of a life insurance company in order to understand its risk, solvency and/or capital requirements.In this paper we describe a genetic algorithm developed to solve the generic selection task. We demonstrate the algorithm successfully solving our test problem.