SOLNP+: A Derivative-Free Solver for Constrained Nonlinear Optimization
Dongdong Ge, Tianhao Liu, Jinsong Liu, Jiyuan Tan, Yinyu Ye
TL;DR
SOLNP+ is an improved, derivative-free solver for constrained nonlinear optimization that enhances robustness and efficiency through new techniques, making it suitable for noisy problems and available as open-source software.
Contribution
It introduces a new version of SOLNP with advanced techniques like implicit filtering and modern quadratic programming, improving performance over previous MATLAB implementations.
Findings
Faster running time compared to previous versions
Enhanced robustness under noisy conditions
Open-source implementation available
Abstract
SOLNP+ is a derivative-free solver for constrained nonlinear optimization. It starts from SOLNP proposed in 1989 by Ye Ye with the main idea that uses finite difference to approximate the gradient. We incorporate the techniques of implicit filtering, new restart mechanism and modern quadratic programming solver into this new version with an ANSI C implementation. The algorithm exhibits a great advantage in running time and robustness under noise compared with the last version by MATLAB. SOLNP+ is free to download at https://github.com/COPT-Public/SOLNP_plus.
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Taxonomy
TopicsAdvanced Optimization Algorithms Research · Matrix Theory and Algorithms · Advanced Adaptive Filtering Techniques