Fuzzy nonlinear programming for mixed-discrete design optimization through hybrid genetic algorithm

Journal article

Peer reviewed

YING YING XIONG and Singiresu S RAO

Fuzzy sets and systems, Vol.146(2), pp.167-186

2004

Abstract

Miscellaneous

Telecommunications and information theory

Exact sciences and technology

Electronics

Information, signal and communications theory

Circuit properties

Electric, optical and optoelectronic circuits

System theory

Digital circuits

Mathematical methods

Computer science; control theory; systems

Theoretical computing

Applied sciences

Control theory. Systems

Electronic circuits

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Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.84 Supply Chain & Logistics; 4.84.1014 MINLP
Web Of Science research areas: Computer Science, Theory & Methods; Mathematics, Applied; Statistics & Probability
ESI research areas: Engineering

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Title: Fuzzy nonlinear programming for mixed-discrete design optimization through hybrid genetic algorithm
Creators: YING YING XIONG - Department of Mechanical Engineering, University of Miami, Coral Gables, FL 33124-0624, United States
Singiresu S RAO - Department of Mechanical Engineering, University of Miami, Coral Gables, FL 33124-0624, United States
Publication Details: Fuzzy sets and systems, Vol.146(2), pp.167-186
Publisher: Elsevier; Amsterdam
Academic Unit: College of Engineering; CoE - Mechanical & Aerospace Engineering
Language: English
Resource Type: Journal article
Record Identifier: 991031578511802976