Solving discrete deceptive problems with EMMRS

ABSTRACT

This paper presents a new method for solving discrete deceptive problems using a genotype to phenotype mapping where a new replacement and shift operator is applied. The method is evaluated using different deceptive problems. Experimental results show how our method obtains a speed-up of 94% with respect to other approaches.

REFERENCES

• 1: R. Chow. 2004. Evolving Genotype to Phenotype Mappings with a Multiple-Chromosome Genetic Algorithm. In GECCO 2004, LNCS 3102, 1006--101 Springer.
• 2: P. Schwefel. 1981. Numerical Optimization of Computer Models. John Wiley & Sons. English translation of Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie, 1977.
• 3: Aimo Torn , Antanas Zilinskas, Global optimization, Springer-Verlag New York, Inc., New York, NY, 1989

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Heuristic methods

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Global optimization

General Terms:
Algorithms, Measurement

Keywords:
deceptive problems, genetic algorithms, genotype and phenotype mapping