Solving Integer Programming Problems Using Genetic Algorithms

  • Anh Huy Pham Nguyen (Faculty or Inoformation Technologies, Natural Sciences University) ;
  • Bich San Chu Tat (Faculty or Inoformation Technologies, Natural Sciences University) ;
  • Triantaphyllou E (Department of Industrial Engineering, Louisiana State University)
  • Published : 2004.08.01

Abstract

There are many methods to find solutions for Integer Programming problems (IPs) such as the Branch-Bound philosophy or the Cutting Plane algorithm. However, most of them have a problem that is the explosion of sets in the computing process. In addition, GA is known as a heuristic search algorithm for solutions of optimization problems. It is started from a random initial guess solution and attempting to find one that is the best under some criteria and conditions. The paper will study an artificial intelligent method to solve IPs by using Genetic Algorithms (GAs). The original solution of this was presented in the papers of Fabricio Olivetti de Francaand and Kimmo Nieminen [2003]. However, both have several limitations which causes could be operations in GAs. The paper proposes a method to upgrade these operations and computational results are also shown to support these upgrades.

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