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In this work, we will present derivative-free versions of the Local Simplex Algorithm (LSA) for finding a local minimum of a real-valued concave function which can be smooth or non-smooth over two types of polyhedrons: box-constraints, linear equality constraints and non-negative variables. Finally, we give some numerical examples and preliminary numerical experiments which illustrate the algorithm and we discuss some extensions.

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A Derivative-Free Simplex Algorithm for the Local Minimization of a Concave Program, with Some Extensions

  • 会议论文

  • 发表日期：

    2026年

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  • Mohand Bentobache

摘要

In this work, we will present derivative-free versions of the Local Simplex Algorithm (LSA) for finding a local minimum of a real-valued concave function which can be smooth or non-smooth over two types of polyhedrons: box-constraints, linear equality constraints and non-negative variables. Finally, we give some numerical examples and preliminary numerical experiments which illustrate the algorithm and we discuss some extensions.