Algorithm Comparison Chart

PHX Optimizers

Algorithm	Multi-Objective	Max # of Objectives	Discrete Variables	Num of function evaluations for convergence	Constraints	Non-smooth responses	Minimize or Maximize	Solve for	Handles failed runs
OPTLIB Gradient Optimizer	false	1	false	very	true	false	true	false	false
Design Explorer	false	1	false	moderate	true	maybe	true	false	true
Darwin	true	-1	true	many	true	true	true	false	true

DOT

Algorithm	Multi-Objective	Max # of Objectives	Discrete Variables	Num of function evaluations for convergence	Constraints	Non-smooth responses	Minimize or Maximize	Solve for	Handles failed runs
DOT SQP	false	1	false	small	true	false	true	false	false
DOT SLP	false	1	false	small	true	false	true	false	false
DOT MMFD	false	1	false	small	true	false	true	false	false
DOT BFGS	false	1	false	small	false	false	true	false	false
DOT FR	false	1	false	small	false	false	true	false	false
BIGDOT	false	1	false	small	true	false	true	false	false

A Collection of Non-gradient Optimizers

Algorithm	Multi-Objective	Max # of Objectives	Discrete Variables	Num of function evaluations for convergence	Constraints	Non-smooth responses	Minimize or Maximize	Solve for	Handles failed runs
Hooke-Jeeves	false	1	false	moderate	false	maybe	true	false	true
Nelder-Mead	false	1	false	moderate	false	maybe	true	false	false
NSGA II	true	-1	true	many	true	true	true	false	true
EVOLVE	false	1	true	many	true	true	true	false	false

SwarmOps

Algorithm	Multi-Objective	Max # of Objectives	Discrete Variables	Num of function evaluations for convergence	Constraints	Non-smooth responses	Minimize or Maximize	Solve for	Handles failed runs
SwarmOps DE	false	1	false	many	true	maybe	true	false	false
SwarmOps DESuite	false	1	false	many	true	maybe	true	false	false
SwarmOps JDE	false	1	false	many	true	maybe	true	false	false
SwarmOps PSO	false	1	false	not very	true	maybe	true	false	false
SwarmOps MOL	false	1	false	many	true	maybe	true	false	false
SwarmOps PS	false	1	false	moderate	true	maybe	true	false	true
SwarmOps LUS	false	1	false	moderate	true	maybe	true	false	true
SwarmOps RND	false	1	false	many	true	true	true	false	true

DAKOTA

Algorithm	Multi-Objective	Max # of Objectives	Discrete Variables	Num of function evaluations for convergence	Constraints	Non-smooth responses	Minimize or Maximize	Solve for	Handles failed runs
DAKOTA APPS	false	1	false	moderate	true	maybe	true	false	false
DAKOTA Coliny DIRECT	false	1	false	moderate	true (fixed penalty)	true	true	false	false
DAKOTA EA	false	1	true	many	true (penalty function)	true	true	false	false
DAKOTA Coliny PS	false	1	false	moderate	true (adaptive penalty function)	maybe	true	false	false
DAKOTA Coliny SW	false	1	false	moderate	true (adaptive penalty function)	maybe	true	false	false
DAKOTA CONMIN	false	1	false	very	true	false	true	false	false
DAKOTA MOGA	true	-1	true	many	true	true	true	false	false
DAKOTA NCSU DIRECT	false	1	false	moderate	false	true	true	false	false
DAKOTA OPT++ Finite Difference Newton	false	1	false	very	true	false	true	false	false
DAKOTA OPT++ Quasi Newton	false	1	false	very	true	false	true	false	false
DAKOTA OPT++ PDS	false	1	false	very	true	false	true	false	false