Experimental Analysis of Optimization Algorithms

Catherine C. McGeoch

ABSTRACT

This chapter surveys methodological issues that arise in experimental research on optimization algorithms. Guidelines are presented for selecting research problems, input classes, and program metrics; for ensuring correctness and reproducibility of the results; for applying appropriate data analysis techniques; and for presenting informative and convincing conclusions. The chapter contains many references to related work on these topics.