EconPapers    
Economics at your fingertips  
 

Simulation Optimization

Jack Kleijnen ()

Chapter 6 in Design and Analysis of Simulation Experiments, 2015, pp 241-300 from Springer

Abstract: Abstract This chapter is organized as follows. Section 6.1 introduces the optimization of real systems that are modeled through either deterministic or random simulation; this optimization we call simulation optimization or briefly optimization. There are many methods for this optimization, but we focus on methods that use specific metamodels of the underlying simulation models; these metamodels were detailed in the preceding chapters, and use either linear regression or Kriging. Section 6.2 discusses the use of linear regression metamodels for optimization. Section 6.2.1 summarizes basic response surface methodology (RSM), which uses linear regression; RSM was developed for experiments with real systems. Section 6.2.2 adapts this RSM to the needs of random simulation. Section 6.2.3 presents the adapted steepest descent (ASD) search direction. Section 6.2.4 summarizes generalized RSM (GRSM) for simulation with multiple responses. Section 6.2.5 summarizes a procedure for testing whether an estimated optimum is truly optimal—using the Karush-Kuhn-Tucker (KKT) conditions. Section 6.3 discusses the use of Kriging metamodels for optimization. Section 6.3.1 presents efficient global optimization (EGO), which uses Kriging. Section 6.3.2 presents Kriging and integer mathematical programming (KrIMP) for the solution of problems with constrained outputs. Section 6.4 discusses robust optimization (RO), which accounts for uncertainties in some inputs. Section 6.4.1 discusses RO using RSM, Sect. 6.4.2 discusses RO using Kriging, and Sect. 6.4.3 summarizes the Ben-Tal et al. approach to RO. Section 6.5 summarizes the major conclusions of this chapter, and suggests topics for future research. The chapter ends with Solutions of exercises, and a long list of references.

Keywords: Response Surface Methodology; Robust Optimization; Pareto Frontier; Goal Function; Input Combination (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (5)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Chapter: Simulation optimization (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-18087-8_6

Ordering information: This item can be ordered from
http://www.springer.com/9783319180878

DOI: 10.1007/978-3-319-18087-8_6

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:isochp:978-3-319-18087-8_6