Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Fuzzy approach to economic analysis of dispatcher driven discrete transport systems
DEPCOS-RELCOMEX '06 Proceedings of the International Conference on Dependability of Computer Systems
Neural Network Device for Reliability and Functional Analysis of Discrete Transport System
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Soft computing approach to discrete transport system management
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
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The essential problem in transport system functional and economic analysis is a technique of modeling the human dispatcher presented in real systems. It is very hard to find an ”intelligent” algorithm of dispatcher – an algorithm which is giving results which significantly differs from pure random algorithms. In a paper we propose an evolutionary approach to this problem. A set of heuristic rules for dispatcher is searched by genetic algorithm. The fitness function is defined by the economic measure. The discrete transport system is modeled using Monte-Carlo simulation. A more accurate model of dispatcher, found by genetic algorithm, allows to obtain more realistic results of functional and economic analysis. The proposed, novelty approach can serve for practical solving of essential decision problems related to an organization and parameters of transport systems.