An Almost Feasible Sequential Linear Programming Algorithm

Fuente: arXiv
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Autores principales: Kiessling, David, Vanaret, Charlie, Astudillo, Alejandro, Decre, Wilm, Swevers, Jan
Formato: Preprint
Publicado: 2024
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author Kiessling, David
Vanaret, Charlie
Astudillo, Alejandro
Decre, Wilm
Swevers, Jan
author_facet Kiessling, David
Vanaret, Charlie
Astudillo, Alejandro
Decre, Wilm
Swevers, Jan
contents This paper proposes an almost feasible Sequential Linear Programming (afSLP) algorithm. In the first part, the practical limitations of previously proposed Feasible Sequential Linear Programming (FSLP) methods are discussed along with illustrative examples. Then, we present a generalization of FSLP based on a tolerance-tube method that addresses the shortcomings of FSLP. The proposed algorithm afSLP consists of two phases. Phase I starts from random infeasible points and iterates towards a relaxation of the feasible set. Once the tolerance-tube around the feasible set is reached, phase II is started and all future iterates are kept within the tolerance-tube. The novel method includes enhancements to the originally proposed tolerance-tube method that are necessary for global convergence. afSLP is shown to outperform FSLP and the state-of-the-art solver IPOPT on a SCARA robot optimization problem.
format Preprint
id arxiv_https___arxiv_org_abs_2401_13840
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An Almost Feasible Sequential Linear Programming Algorithm
Kiessling, David
Vanaret, Charlie
Astudillo, Alejandro
Decre, Wilm
Swevers, Jan
Optimization and Control
This paper proposes an almost feasible Sequential Linear Programming (afSLP) algorithm. In the first part, the practical limitations of previously proposed Feasible Sequential Linear Programming (FSLP) methods are discussed along with illustrative examples. Then, we present a generalization of FSLP based on a tolerance-tube method that addresses the shortcomings of FSLP. The proposed algorithm afSLP consists of two phases. Phase I starts from random infeasible points and iterates towards a relaxation of the feasible set. Once the tolerance-tube around the feasible set is reached, phase II is started and all future iterates are kept within the tolerance-tube. The novel method includes enhancements to the originally proposed tolerance-tube method that are necessary for global convergence. afSLP is shown to outperform FSLP and the state-of-the-art solver IPOPT on a SCARA robot optimization problem.
title An Almost Feasible Sequential Linear Programming Algorithm
topic Optimization and Control
url https://arxiv.org/abs/2401.13840