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since 2007/10/24

The page is obsolete, we have moved to openopt.org

Least squares problems (LSP)

F₀(x)²+F₁(x)²+...+F_m(x)² -> min,
x from Rⁿ

subjected to

• Box - bound constraints
  • lb <= x <= ub (some coords of lb and ub can be +/- inf)
    
• General linear constraints
  • A*x <= b
    
  • Aeq*x = beq
    
• Non-linear constraints
  • c_i(x) <= 0, i = 0...I
    
  • h_j(x) = 0, j = 0...J
    

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Note! Since OpenOpt v. 0.21 LSP has been renamed to NLLSP (Non-linear least squares problem)

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OpenOpt LSP example >>>

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LSP solvers

Solver	License	Made by	Info
scipy_leastsq	BSD	Argonne national laboratory, Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. more	Unconstrained problems only! "leastsq" is a scipy wrapper around MINPACK's lmdif algorithm
converter to nlp		Dmitrey	Example: r = p.solve('nlp:ralg'). See NLP page for list of available NLP solvers