@inproceedings{2eff363ef65e49e082356213f4b8222f,
title = "Fuzzy heuristics for sequential linear programming",
abstract = "Numerical implementations of optimization algorithms often use parameters whose values are not strictly determined by the derivation of the algorithm, but must fall in some appropriate range of values. This work describes how fuzzy logic can be used to control such parameters to improve algorithms performance. This concept is shown with the use of sequential linear programming (SLP) due to its simplicity in implementation. The algorithm presented in this paper implements heuristics to improve the behavior of SLP based on current iterate values of design constraints and changes in search direction. Fuzzy logic is used to implement the heuristics in a form similar to what a human observer would do. An efficient algorithm, known as the infeasible primal-dual path-following interior-point method, is used for solving the sequence of LP problems. Four numerical examples are presented to show that the proposed SLP algorithm consistently performs better than the standard SLP algorithm.",
keywords = "Fuzzy control, Fuzzy heuristics, Optimization, Parameter adaptation, Sequential linear programming, Slp",
author = "Mulkay, {Eric L.} and Rao, {Singiresu S.}",
note = "Publisher Copyright: {\textcopyright} 1997 by ASME.; ASME 1997 Design Engineering Technical Conferences, DETC 1997 ; Conference date: 14-09-1997 Through 17-09-1997",
year = "1997",
doi = "10.1115/DETC97/DAC-3966",
language = "English (US)",
series = "Proceedings of the ASME Design Engineering Technical Conference",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "23rd Design Automation Conference",
}