Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms | Zendy

Luigi Maria Galantucci | Zendy; Gianluca Percoco | Zendy; Roberto Spina | Zendy

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Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

Author(s) -

Luigi Maria Galantucci,

Gianluca Percoco,

Roberto Spina

Publication year - 2004

Publication title -

international journal of advanced robotic systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.394

H-Index - 46

eISSN - 1729-8814

pISSN - 1729-8806

DOI - 10.5772/5622

Subject(s) - crossover , computer science , fuzzy logic , genetic algorithm , sequence (biology) , algorithm , controller (irrigation) , process (computing) , artificial intelligence , machine learning , genetics , agronomy , biology , operating system

The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of the optimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies

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