A stigmergy-based algorithm for black-box optimization: noiseless function testbed

ABSTRACT

In this paper, we present a stigmergy-based algorithm for solving optimization problems with continuous variables, labeled Differential Ant-Stigmergy Algorithm (DASA). The performance of the DASA is evaluated on the set of benchmark problems provided for Black-Box Optimization Benchmarking (BBOB) 2009, a GECCO Workshop for Real-Parameter Optimization. Benchmarking for noiseless function testbed is presented.

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INDEX TERMS

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

Additional Classification:
  F. Theory of Computation
  F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY
      F.2.1 Numerical Algorithms and Problems

  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Unconstrained optimization

General Terms:
Algorithms

Keywords:
benchmarking, black-box optimization, stigmergy