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Title: XROUTE: A knowledge-based routing system using neural networks and genetic algorithms

Abstract

This dissertation is concerned with applying alternative methods of artificial intelligence (AI) in conjunction with mathematical methods to Vehicle Routing Problems. The combination of good mathematical models, knowledge-based systems, artificial neural networks, and adaptive genetic algorithms (GA) - which are shown to be synergistic - produces near-optimal results, which none of the individual methods can produce on its own. A significant problem associated with application of the Back Propagation learning paradigm for pattern classification with neural networks is the lack of high accuracy in generalization when the domain is large. In this work, a multiple neural network system is employed, using two self-organizing neural networks that work as feature extractors, producing information that is used to train a generalization neural network. The technique was successfully applied to the selection of control rules for a Traveling Salesman Problem heuristic, thus making it adaptive to the input problem instance. XROUTE provides an interactive visualization system, using state-of-the-art vehicle routing models and AI tools, yet allows an interactive environment for human expertise to be utilized in powerful ways. XROUTE provides an experimental, exploratory framework that allows many variations, and alternatives to problems with different characteristics. XROUTE is dynamic, expandable, and adaptive, and typicallymore » outperforms alternative methods in computer-aided vehicle routing.« less

Authors:
Publication Date:
Research Org.:
North Dakota State Univ., Fargo, ND (United States)
OSTI Identifier:
6087250
Resource Type:
Miscellaneous
Resource Relation:
Other Information: Thesis (Ph.D)
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ARTIFICIAL INTELLIGENCE; USES; NEURAL NETWORKS; VEHICLES; ROUTING; ALGORITHMS; COMPUTER ARCHITECTURE; COMPUTERIZED SIMULATION; INTERACTIVE DISPLAY DEVICES; KNOWLEDGE BASE; MAN-MACHINE SYSTEMS; ROAD TRANSPORT; X CODES; COMPUTER CODES; COMPUTER OUTPUT DEVICES; COMPUTER-GRAPHICS DEVICES; DISPLAY DEVICES; LAND TRANSPORT; MATHEMATICAL LOGIC; SIMULATION; TRANSPORT; 990200* - Mathematics & Computers

Citation Formats

Kadaba, N. XROUTE: A knowledge-based routing system using neural networks and genetic algorithms. United States: N. p., 1990. Web.
Kadaba, N. XROUTE: A knowledge-based routing system using neural networks and genetic algorithms. United States.
Kadaba, N. Mon . "XROUTE: A knowledge-based routing system using neural networks and genetic algorithms". United States.
@article{osti_6087250,
title = {XROUTE: A knowledge-based routing system using neural networks and genetic algorithms},
author = {Kadaba, N},
abstractNote = {This dissertation is concerned with applying alternative methods of artificial intelligence (AI) in conjunction with mathematical methods to Vehicle Routing Problems. The combination of good mathematical models, knowledge-based systems, artificial neural networks, and adaptive genetic algorithms (GA) - which are shown to be synergistic - produces near-optimal results, which none of the individual methods can produce on its own. A significant problem associated with application of the Back Propagation learning paradigm for pattern classification with neural networks is the lack of high accuracy in generalization when the domain is large. In this work, a multiple neural network system is employed, using two self-organizing neural networks that work as feature extractors, producing information that is used to train a generalization neural network. The technique was successfully applied to the selection of control rules for a Traveling Salesman Problem heuristic, thus making it adaptive to the input problem instance. XROUTE provides an interactive visualization system, using state-of-the-art vehicle routing models and AI tools, yet allows an interactive environment for human expertise to be utilized in powerful ways. XROUTE provides an experimental, exploratory framework that allows many variations, and alternatives to problems with different characteristics. XROUTE is dynamic, expandable, and adaptive, and typically outperforms alternative methods in computer-aided vehicle routing.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1990},
month = {1}
}

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