Discrete optimization with fuzzy constraints

Primož Jelušič (Avtor), Bojan Žlender (Avtor)

Povzetek

The primary benefit of fuzzy systems theory is to approximate system behavior where analytic functions or numerical relations do not exist. In this paper, heuristic fuzzy rules were used with the intention of improving the performance of optimization models, introducing experiential rules acquired from experts and utilizing recommendations. The aim of this paper was to define soft constraints using an adaptive network-based fuzzy inference system (ANFIS). This newly-developed soft constraint was applied to discrete optimization for obtaining optimal solutions. Even though the computational model is based on advanced computational technologies including fuzzy logic, neural networks and discrete optimization, it can be used to solve real-world problems of great interest for design engineers. The proposed computational model was used to find the minimum weight solutions for simply-supported laterally-restrained beams.

Ključne besede

negotovost;diskretno optimiranje;sinteza konstrukcij;optimizacija;uncertainty;discrete optimization;neuro-fuzzy technique;structural optimization;

Podatki

Jezik:	Angleški jezik
Leto izida:	2017
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	UM FGPA - Fakulteta za gradbeništvo, prometno inženirstvo in arhitekturo
UDK:	624.04:004.8
COBISS:	20691222
ISSN:	2073-8994
Matična publikacija:	Symmetry
Št. ogledov:	937
Št. prenosov:	332
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Slovenski jezik
Sekundarne ključne besede:	negotovost;diskretno optimiranje;sinteza konstrukcij;optimizacija;
URN:	URN:SI:UM:
Vrsta dela (COBISS):	Znanstveno delo
Strani:	str. 1-22
Letnik:	ǂVol. ǂ9
Zvezek:	ǂiss. ǂ6
Čas izdaje:	June 2017
DOI:	10.3390/sym9060087
ID:	10852869