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The Rsolnp package implements Y.Ye's general nonlinear augmented Lagrange multiplier method solver (SQP based solver).
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● Keywords:
● Alias: Rsolnp, Rsolnp-package
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The function implements a set of benchmark problems against the MINOS solver of Murtagh and Saunders.
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● Keywords: optimize
● Alias: benchmark
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The solnp function is based on the solver by Yinyu Ye which solves the general nonlinear programming problem:
● Data Source:
CranContrib
● Keywords: optimize
● Alias: solnp
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A simple penalty barrier function is formed which is then evaluated at randomly sampled points based on the upper and lower parameter bounds (when eval.type = 2), else the objective function directly for values not violating any inequality constraints (when eval.type = 1). The sampled points can be generated from the uniform, normal or truncated normal distributions.
● Data Source:
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● Keywords: optimize
● Alias: startpars
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Returns the id's of available benchmark in the Rsolnp Benchmark Problems Suite.
● Data Source:
CranContrib
● Keywords: optimize
● Alias: benchmarkids
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When the objective function is non-smooth or has many local minima, it is hard to judge the optimality of the solution, and this usually depends critically on the starting parameters. This function enables the generation of a set of randomly chosen parameters from which to initialize multiple restarts of the solver (see note for details).
● Data Source:
CranContrib
● Keywords: optimize
● Alias: gosolnp
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providing 
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