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FPGA-Based Implementation of Genetic Algorithm for the Traveling Salesman Problem and Its Industrial Application
Author(s) -
Iouliia Skliarova,
A. Ferrari
Publication year - 2002
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-43781-9
DOI - 10.1007/3-540-48035-8_9
Subject(s) - travelling salesman problem , computer science , genetic algorithm , point (geometry) , set (abstract data type) , field programmable gate array , controller (irrigation) , realization (probability) , motion control , 2 opt , algorithm , mathematical optimization , artificial intelligence , embedded system , robot , mathematics , machine learning , agronomy , biology , programming language , statistics , geometry
In this paper an adaptive distribution system for manufacturing applications is considered and examined. The system receives a set of various components at a source point and supplies these components to destination points. The objective is to minimize the total distance that has to be traveled. At each destination point some control algorithms have to be activated and each segment of motion between destination points has also to be controlled. The paper suggests a model for such a distribution system based on autonomous subalgorithms that can further be linked hierarchically. The links are set up during execution time (during motion) with the aid of the results obtained from solving the respective traveling salesman problem (TSP) that gives a proper tour of minimal length. The paper proposes an FPGA-based solution, which integrates a specialized virtual controller implementing hierarchical control algorithms and a hardware realization of genetic algorithm for the TSP.

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