Hybrid Approach to Reliability and Functional Analysis of Discrete Transport System

Abstract

AbstractThis paper describes a novel approach of combining Monte Carlo simulation and neural nets. This hybrid approach is applied to model discrete transportation systems, with the accurate but computationally expensive Monte Carlo simulation used to train a neural net. Once trained the neural net can efficiently, but less accurately provide functional analysis and reliability predictions. No restriction on the system structure and on a kind of distribution is the main advantage of the proposed approach. The results of reliability and functional analysis can be used as a basis for economic aspects discussion related to the discrete transport system. The presented decision problem is practically essential for defining an organization of vehicle maintenance.KeywordsHybrid ApproachService Level AgreementRepair TimeInput QueueSingle RoadThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.