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since 2007/10/24

Linear Least Absolute Value Problem (LLAVP)

(aka LLADP - Linear Least Absolute Deviation Problem)

    ||C*x-d||1 + damp*||x-X||1 -> min

subjected to

• Box - bound constraints
  • lb <= x <= ub (some coords of lb and ub can be +/- inf)
    

(some more constraints will be added if appropriate solver(s) will be connected)

Required data: C, d

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Note! If damp is provided (by user) but vector X is not, then X is filled by zeros.

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OpenOpt LLAVP example >>>

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LLAVP solvers

Solver	License	Optional data that can be handled	Sparsity handling	Made By	Info
converter to nsp	-	those that can be handled by the NSP solver involved	?	Dmitrey	Example: r = p.solve('nlp:ralg', plot=1). Recommended solvers: ralg, ipopt