Pareto-optimal set based multiobjective tuning of fuzzy automatic train operation for mass transit system
نویسندگان
چکیده
A novel approach of differential evolution (DE) by incorporating the Pareto-optimal set is presented for optimising train movement through tuning fuzzy membership functions in mass transit systems. The Pareto-optimal based multiobjective optimisation approach uniquely provides a set of optimal non-dominated solutions to the decision-maker. From the set, the decision-maker selects satisfactory solutions according to different running conditions to meet the various requirements. A fuzzy controller for automatic train operation is optimised to demonstrate the effectiveness of this new approach. List of major symbols NP = number of populations T = maximum permitted number of generations ξ = amplification probability in DE CR = crossover probability in DE δ = penalty factor in DE λ = desired minimal separation parameter SP = safety performance index P = punctuality performance index RC = riding comfort performance index ES = energy saving performance index
منابع مشابه
Optimal design of energy-efficient ATO CBTC driving for metro lines based on NSGA-II with fuzzy parameters
One of the main priorities for metro line operators is the reduction of energy consumption, due to the environmental impact and economic cost. The new moving block signalling system CBTC (Communication Based Train Control) is being installed in order to increase the transport capacity of new metro lines, and to upgrade lines equipped with the former fixed block signalling systems. In addition, ...
متن کاملA Fuzzy Control for Train Automatic Stop Control†
A predictive fuzzy control system that uses rules based on the experience of a skilled human operator is proposed and applied to achieve automatic stop operation for trains. In recent years, automatic train operation (ATO) systems using microcomputers to replace human operators have been developed for new transit systems, including subways, monorails and new public transit systems. Because the ...
متن کاملA Novel Multiobjective Evolutionary Algorithm for Solving Environmental/economic Dispatch Problem
This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective problem with competing and non-commensurable objectives....
متن کاملEnvironmental/Economic Power Dispatch Using Multiobjective Evolutionary Algorithms
This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the EED as a true multiobjective optimization problem with competing and noncommensurable obj...
متن کاملEvolutionary Multiobjective Optimization for Fuzzy Knowledge Extraction
− A new trend in the design of fuzzy rulebased systems is the use of evolutionary multiobjective optimization (EMO) algorithms. This trend is observed in various areas in machine learning. EMO algorithms are often used to search for a number of Pareto-optimal non-linear systems with respect to their accuracy and complexity. In this paper, we first explain some basic concepts in multiobjective o...
متن کامل