Optimal design of energy-efficient ATO CBTC driving for metro lines based on NSGA-II with fuzzy parameters
暂无分享,去创建一个
Antonio Fernández-Cardador | William Carvajal-Carreño | Asunción Paloma Cucala García | A. Fernández-Cardador | William Carvajal-Carreño
[1] Chun-Liang Lin,et al. Optimisation of train energy-efficient operation for mass rapid transit systems , 2012 .
[2] H. B. Quek,et al. Pareto-optimal set based multiobjective tuning of fuzzy automatic train operation for mass transit system , 1999 .
[3] Didier Dubois,et al. Ranking fuzzy numbers in the setting of possibility theory , 1983, Inf. Sci..
[4] Tin Kin Ho,et al. Coast control for mass rapid transit railways with searching methods , 2004 .
[5] Eugene Khmelnitsky,et al. On an optimal control problem of train operation , 2000, IEEE Trans. Autom. Control..
[6] C. S. Chang,et al. Differential evolution based tuning of fuzzy automatic train operation for mass rapid transit system , 2000 .
[7] Nils Brunsson. My own book review : The Irrational Organization , 2014 .
[8] M. Guerrieri,et al. A Logic Fuzzy Model for Evaluation of the Railway Station’s Practice Capacity in Safety Operating Conditions , 2013 .
[9] R. R. Pecharromán,et al. Energy Savings in Metropolitan Railway Substations Through Regenerative Energy Recovery and Optimal Design of ATO Speed Profiles , 2012, IEEE Transactions on Automation Science and Engineering.
[10] Xuesong Feng,et al. Rational Formations of a Metro Train Improve Its Efficiencies of Both Traction Energy Utilization and Passenger Transport , 2013 .
[11] Piotr Lukaszewicz,et al. Optimal design of metro automatic train operation speed profiles for reducing energy consumption , 2011 .
[12] Paul Martin,et al. Train performance and simulation , 1999, WSC '99.
[13] Andrew M. Tobias,et al. Reduction of train and net energy consumption using genetic algorithms for Trajectory Optimisation , 2010 .
[14] Baohua Mao,et al. Simulation Algorithm for Energy-Efficient Train Control under Moving Block System , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.
[15] M. Meyer,et al. An algorithm for the optimal control of the driving of trains , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).
[16] Masafumi Miyatake,et al. Application of dynamic programming to the optimization of the running profile of a train , 2004 .
[17] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[18] Ziyou Gao,et al. Optimization Method of Energy Saving Train Operation for Railway Network , 2009 .
[19] Tae Won Park,et al. Operating speed pattern optimization of railway vehicles with differential evolution algorithm , 2013 .
[20] S. Chanas,et al. A fuzzy approach to the transportation problem , 1984 .
[21] Pandian Vasant,et al. HYBRID SIMULATED ANNEALING AND GENETIC ALGORITHMS FOR INDUSTRIAL PRODUCTION MANAGEMENT PROBLEMS , 2009 .
[22] Tin Kin Ho,et al. Coast control of train movement with genetic algorithm , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[23] Tao Tang,et al. Energy saving for automatic train control in moving block signaling system , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).
[24] Piotr Lukaszewicz,et al. Modeling and optimizing energy‐efficient manual driving on high‐speed lines , 2012 .
[25] Kaisa Miettinen,et al. PAINT: Pareto front interpolation for nonlinear multiobjective optimization , 2012, Comput. Optim. Appl..
[26] A. Fernandez,et al. Energy-saving Automatic Optimisation Of TrainSpeed Commands Using Direct Search Techniques , 1970 .
[27] R.D. Pascoe,et al. What is communication-based train control? , 2009, IEEE Vehicular Technology Magazine.
[28] Antonio Fernández-Cardador,et al. Fuzzy optimal schedule of high speed train operation to minimize energy consumption with uncertain delays and driver's behavioral response , 2012, Eng. Appl. Artif. Intell..
[29] Xiang Li,et al. Optimization of Multitrain Operations in a Subway System , 2014, IEEE Transactions on Intelligent Transportation Systems.
[30] Rafael Castro-Linares,et al. Trajectory tracking for non-holonomic cars: A linear approach to controlled leader-follower formation , 2010, 49th IEEE Conference on Decision and Control (CDC).
[31] Fan Yang,et al. A Differential Evolution Variant of NSGA II for Real World Multiobjective Optimization , 2007, ACAL.
[32] Chao-Shun Chen,et al. Design of Optimal Coasting Speed for MRT Systems Using ANN Models , 2009 .
[33] Pandian Vasant,et al. Hybrid Tabu Search Hopfield Recurrent ANN Fuzzy Technique to the Production Planning Problems: A Case Study of Crude Oil in Refinery Industry , 2012, Int. J. Manuf. Mater. Mech. Eng..
[34] Chun-Liang Lin,et al. Block-Layout Design Using MAX–MIN Ant System for Saving Energy on Mass Rapid Transit Systems , 2009, IEEE Transactions on Intelligent Transportation Systems.
[35] Bin Xu,et al. A Review Study on Traction Energy Saving of Rail Transport , 2013 .
[36] Marco Farina,et al. A fuzzy definition of "optimality" for many-criteria optimization problems , 2004, IEEE Trans. Syst. Man Cybern. Part A.
[37] Miguel A. Salido,et al. Distributed search in railway scheduling problems , 2008, Eng. Appl. Artif. Intell..
[38] Masafumi Miyatake,et al. Optimization of Train Speed Profile for Minimum Energy Consumption , 2010 .
[39] Joshua D. Knowles,et al. On metrics for comparing nondominated sets , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[40] Witold Pedrycz,et al. Energy-efficient differentiated coverage of dynamic objects using an improved evolutionary multi-objective optimization algorithm with fuzzy-dominance , 2012, 2012 IEEE Congress on Evolutionary Computation.
[41] Amie R. Albrecht,et al. Energy-efficient train control: From local convexity to global optimization and uniqueness , 2013, Autom..
[42] Pandian Vasant,et al. Improved Tabu Search Recursive fuzzy method for Crude Oil Industry , 2012, Int. J. Model. Simul. Sci. Comput..
[43] Tin-Kin Ho,et al. A prioritized fuzzy constraint satisfaction approach to model agent negotiation for railway scheduling , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).
[44] M. T. Isaai,et al. Intelligent timetable evaluation using fuzzy AHP , 2011, Expert Syst. Appl..
[45] Ajith Abraham,et al. An improved Multiobjective Evolutionary Algorithm based on decomposition with fuzzy dominance , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[46] Clive Roberts,et al. Optimal driving strategy for traction energy saving on DC suburban railways , 2007 .
[47] Kalyanmoy Deb,et al. Improved Pruning of Non-Dominated Solutions Based on Crowding Distance for Bi-Objective Optimization Problems , 2006, 2006 IEEE International Conference on Evolutionary Computation.
[48] Tad Gonsalves,et al. Multi objective particle swarm optimization algorithm for the design of efficient ATO speed profiles in metro lines , 2014, Eng. Appl. Artif. Intell..
[49] Jun Zhang,et al. Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms , 2014, IEEE Transactions on Evolutionary Computation.
[50] Xiang Li,et al. Optimizing trains movement on a railway network , 2012 .
[51] Shinya Hanaoka,et al. Multiple Criteria and Fuzzy Based Evaluation of Logistics Performance for Intermodal Transportation , 2009 .
[52] Haidong Liu,et al. A Two-level Optimization Model and Algorithm for Energy-Efficient Urban Train Operation , 2011 .
[53] R. Chen,et al. Development of the new CBTC system simulation and performance analysis , 2010 .
[54] Rémy Chevrier,et al. An evolutionary multi-objective approach for speed tuning optimization with energy saving in railway management , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.
[55] Baohua Mao,et al. Energy-Efficient Locomotive Operation for Chinese Mainline Railways by Fuzzy Predictive Control , 2014, IEEE Transactions on Intelligent Transportation Systems.
[56] Alexander Fay,et al. A fuzzy knowledge-based system for railway traffic control , 2000 .
[57] M. Gupta,et al. Theory of T -norms and fuzzy inference methods , 1991 .
[58] D. C. Gill,et al. A simulation tool to support signalling and train control design for high-capacity railways , 2012 .
[59] C. Yalçin Kaya,et al. A New Scalarization Technique to Approximate Pareto Fronts of Problems with Disconnected Feasible Sets , 2013, Journal of Optimization Theory and Applications.
[60] Tomislav Josip Mlinarić,et al. Energy Efficiency of Railway Lines , 2011 .
[61] Regina Lamedica,et al. Energy management in metro-transit systems: An innovative proposal toward an integrated and sustaina , 2011 .
[62] Joydeep Dutta,et al. A new scalarization and numerical method for constructing the weak Pareto front of multi-objective optimization problems , 2011 .
[63] Sanjoy Das,et al. A Multiobjective Evolutionary-Simplex Hybrid Approach for the Optimization of Differential Equation Models of Gene Networks , 2008, IEEE Transactions on Evolutionary Computation.
[64] P. Martin. Train performance & simulation , 2008 .
[65] Peng Zhou,et al. Train Optimal Control Strategy on Continuous Change Gradient Steep Downgrades , 2011 .
[66] Ching-Ter Chang. An Approximation Approach for Representing S-Shaped Membership Functions , 2010, IEEE Transactions on Fuzzy Systems.
[67] Xiaohong Zhang,et al. Stability Analysis and Design of Time-Varying Nonlinear Systems Based on Impulsive Fuzzy Model , 2012 .
[68] Ziyou Gao,et al. Train Timetable Problem on a Single-Line Railway With Fuzzy Passenger Demand , 2009, IEEE Transactions on Fuzzy Systems.
[69] C. S. Chang,et al. Online rescheduling of mass rapid transit systems: fuzzy expert system approach , 1996 .
[70] Richard Bellman,et al. Decision-making in fuzzy environment , 2012 .
[71] Zhi Xiao,et al. The trapezoidal fuzzy soft set and its application in MCDM , 2012 .
[72] Chung Min Kwan,et al. Application of evolutionary algorithm on a transportation scheduling problem - the mass rapid transit , 2005, 2005 IEEE Congress on Evolutionary Computation.
[73] Li-Min Jia,et al. Distributed intelligent railway traffic control: A fuzzy-decisionmaking-based approach , 1994 .
[74] Marco Laumanns,et al. Computing Gap Free Pareto Front Approximations with Stochastic Search Algorithms , 2010, Evolutionary Computation.
[75] Mehmet Turan Soylemez,et al. Coasting point optimisation for mass rail transit lines using artificial neural networks and genetic algorithms , 2008 .
[76] Limin Jia,et al. A Fuzzy Optimization Model for High-Speed Railway Timetable Rescheduling , 2012 .
[77] Clive Roberts,et al. Single-Train Trajectory Optimization , 2013, IEEE Transactions on Intelligent Transportation Systems.
[78] Bijay Ketan Panigrahi,et al. Multiobjective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatc , 2010 .
[79] Antonio Fernández-Cardador,et al. Real time regulation of efficient driving of high speed trains based on a genetic algorithm and a fuzzy model of manual driving , 2014, Eng. Appl. Artif. Intell..
[80] Bart De Schutter,et al. A survey on optimal trajectory planning for train operations , 2011, Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics.
[81] Laxmidhar Behera,et al. Diversity improvement of solutions in multiobjective genetic algorithms using pseudo function inverses , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.
[82] Chao-Shun Chen,et al. Design of optimal coasting speed for saving social cost in Mass Rapid Transit systems , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.