Derivative-free optimization: a review of algorithms and comparison of software implementations

Abstract This paper addresses the solution of bound-constrained optimization problems using algorithms that require only the availability of objective function values but no derivative information. We refer to these algorithms as derivative-free algorithms. Fueled by a growing number of applications in science and engineering, the development of derivative-free optimization algorithms has long been studied, and it has found renewed interest in recent time. Along with many derivative-free algorithms, many software implementations have also appeared. The paper presents a review of derivative-free algorithms, followed by a systematic comparison of 22 related implementations using a test set of 502 problems. The…

• NS
  National Science Foundation
• NI
  National Institutes of Health
• NE
  National Energy Technology Laboratory

  Awards: DE-FE-0004000, 0004000
• NI
  National Institute of General Medical Sciences
• DO
  Division of Chemical, Bioengineering, Environmental, and Transport Systems