Publication detail

Integer simulation based optimization by local search

SKLENÁŘ, J. POPELA, P.

Original Title

Integer simulation based optimization by local search

English Title

Integer simulation based optimization by local search

Type

journal article - other

Language

en

Original Abstract

Simulation-based optimization combines simulation experiments used to evaluate the objective and/or constraint functions with an optimization algorithm. Compared with classical optimization, simulation based optimization brings its specific problems and restrictions. These are discussed in the paper. Evaluation of the objective function is based on time consuming, typically repeated simulation experiments. So we believe that the main objective in selecting the optimization algorithm is minimization of the number of objective function evaluations. In this paper we concentrate on integer optimization that is typical in simulation context. Local search algorithms that try to minimize the number of objective function evaluations are described. Examples with both analytical and simulationbased objective functions are used to demonstrate the performance of the algorithms.

English abstract

Simulation-based optimization combines simulation experiments used to evaluate the objective and/or constraint functions with an optimization algorithm. Compared with classical optimization, simulation based optimization brings its specific problems and restrictions. These are discussed in the paper. Evaluation of the objective function is based on time consuming, typically repeated simulation experiments. So we believe that the main objective in selecting the optimization algorithm is minimization of the number of objective function evaluations. In this paper we concentrate on integer optimization that is typical in simulation context. Local search algorithms that try to minimize the number of objective function evaluations are described. Examples with both analytical and simulationbased objective functions are used to demonstrate the performance of the algorithms.

Keywords

Integer optimization; Local search; Simulation

Released

30.05.2010

Pages from

1341

Pages to

1348

Pages count

8

Documents

BibTex


@article{BUT124192,
  author="Jaroslav {Sklenář} and Pavel {Popela}",
  title="Integer simulation based optimization by local search",
  annote="Simulation-based optimization combines simulation experiments used to evaluate the objective and/or constraint functions with an optimization algorithm. Compared with classical optimization, simulation based optimization brings its specific problems and restrictions. These are discussed in the paper. Evaluation of the objective function is based on time consuming, typically repeated simulation experiments. So we believe that the main objective in selecting the optimization algorithm is minimization of the number of objective function evaluations. In this paper we concentrate on integer optimization that is typical in simulation context. Local search algorithms that try to minimize the number of objective function evaluations are described. Examples with both analytical and simulationbased objective functions are used to demonstrate the performance of the algorithms.
",
  chapter="124192",
  howpublished="print",
  number="1",
  volume="1",
  year="2010",
  month="may",
  pages="1341--1348",
  type="journal article - other"
}