Loading...

A new metamodel-based method for solving semi-expensive simulation optimization problems

Moghaddam, S ; Sharif University of Technology | 2017

659 Viewed
  1. Type of Document: Article
  2. DOI: 10.1080/03610918.2015.1134567
  3. Publisher: Taylor and Francis Inc , 2017
  4. Abstract:
  5. In this article, a new algorithm for rather expensive simulation problems is presented, which consists of two phases. In the first phase, as a model-based algorithm, the simulation output is used directly in the optimization stage. In the second phase, the simulation model is replaced by a valid metamodel. In addition, a new optimization algorithm is presented. To evaluate the performance of the proposed algorithm, it is applied to the (s,S) inventory problem as well as to five test functions. Numerical results show that the proposed algorithm leads to better solutions with less computational time than the corresponding metamodel-based algorithm. © 2017 Taylor & Francis Group, LLC
  6. Keywords:
  7. Kriging ; Metamodel-based algorithm ; Particle swarm optimization ; Semi-expensive simulation problems ; Simulation optimization ; Particle swarm optimization (PSO) ; Computational time ; Meta model ; Model-based algorithms ; Optimization algorithms ; Simulation outputs ; Optimization
  8. Source: Communications in Statistics: Simulation and Computation ; Volume 46, Issue 6 , 2017 , Pages 4795-4811 ; 03610918 (ISSN)
  9. URL: https://www.tandfonline.com/doi/full/10.1080/03610918.2015.1134567