optim_doc: Scalar optimization

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## 1 Functions for optimization of a scalar objective function

    Frontend
• nonlin_min: |  | Interface for scalar non-linear optimization.
    Backends
• lm_feasible: |  | L/M-like optimizer, constraints met throughout optimization.
• octave_sqp: |  | A wrapper to core Octaves sqp function.
• siman: |  | Simulated annealing with constraints.
• samin: |  | Simulated annealing covering a range.
• d2_min: |  | Newton-like optimizer, no constraints.
    Alternative frontend
• fmins: |  | Frontend for direct search (gradient-less) algorithms.
    Standalone functions
• nmsmax: |  | A Nelder-Mead simplex algorithm.
• mdsmax: |  | A multidirectional search algorithm.
• adsmax: |  | An alternating directions algorithm.
• nelder_mead_min: |  | Another Nelder-Mead algorithm.
• powell: |  | Direction-set (Powell’s) method.
• bfgsmin: |  | Unconstrained BFGS algorithm.
• nrm: |  | Newton-Raphson algorithm.
• cg_min: |  | A conjugate gradient method.
• brent_line_min: |  | Linesearch, Brent method.
• line_min: |  | Linesearch (minimize a function along dx).
• de_min: |  | A differential evolution algorithm.
• battery: |  | Repeatedly call bfgsmin.