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Simulation-Based Optimisation for Autonomous Transportation Systems Using a Parallel Real-Coded Genetic Algorithm with Scalable Nonuniform Mutation

Open Access
|Dec 2021

References

  1. 1. Akopov, A. S., L. A. Beklaryan, A. L. Beklaryan. Cluster-Based Optimization of an Evacuation Process Using a Parallel Bi-Objective Real-Coded Genetic Algorithm. – Cybernetics and Information Technologies, Vol. 20, 2020, No 3, pp. 45-63.10.2478/cait-2020-0027
  2. 2. Akopov, A. S., L. A. Beklaryan, M. Thakur, B. D. Verma. Parallel Multi-Agent Real-Coded Genetic Algorithm for Large-Scale Black-Box Single-Objective Optimisation. – Knowledge-Based Systems, Vol. 174, 2019, pp. 103-122.10.1016/j.knosys.2019.03.003
  3. 3. Akopov, A. S., L. A. Beklaryan, A. K. Saghatelyan. Agent-Based Modelling of Interactions between Air Pollutants and Greenery Using a Case Study of Yerevan, Armenia. – Environmental Modelling and Software, Vol. 116, 2019, pp. 7-25.10.1016/j.envsoft.2019.02.003
  4. 4. Akopov, A. S., L. A. Beklaryan. An Agent Model of Crowd Behavior in Emergencies. – Automation and Remote Control, Vol. 76, 2015, No 10, pp. 1817-1827.10.1134/S0005117915100094
  5. 5. Akopov, A. S. Parallel Genetic Algorithm with Fading Selection. – International Journal of Computer Applications in Technology, Vol. 49, 2014, No 3-4, pp. 325-331.10.1504/IJCAT.2014.062368
  6. 6. Astsatryan, H., A. Kocharyan, D. Hagimont, A. Lalayan. Performance Optimization System for Hadoop and Spark Frameworks. – Cybernetics and Information Technologies, Vol. 20, 2020, No 6, pp. 5-17.10.2478/cait-2020-0056
  7. 7. Audet, C., M. Kokkolaras. Blackbox and Derivative-Free Optimization: Theory, Algorithms and Applications. – Optimization and Engineering, Vol. 17, 2016, No 1, pp. 1-2.10.1007/s11081-016-9307-4
  8. 8. Beklaryan, G. L., A. S. Akopov, N. K. Khachatryan. Optimisation of System Dynamics Models Using a Real-Coded Genetic Algorithm with Fuzzy Control. – Cybernetics and Information Technologies, Vol. 19, 2019, No 2, pp. 87-103.10.2478/cait-2019-0017
  9. 9. Beklaryan, A. L., A. S. Akopov. Simulation of Agent-Rescuer Behaviour in Emergency Based on Modified Fuzzy Clustering. – In: Proceedings of the International Joint Conference on Autonomous Agents and Multigene Systems, AAMAS, 2016, pp. 1275-1276.
  10. 10. Conn, A. R., K. Scheinberg, L. N. Vicente. Introduction to Derivative-Free Optimization. – MPS-SIAM Book Series on Optimization. Philadelphia, SIAM, 2009.10.1137/1.9780898718768
  11. 11. Deep, K., M. Thakur. A New Mutation Operator for Real Coded Genetic Algorithms. – Applied Mathematics and Computation, Vol. 193, 2007, No 1, pp. 211-230.10.1016/j.amc.2007.03.046
  12. 12. Helbing, D. Traffic and Related Self-Driven Many-Particle Systems. – Review of Modern Physics, Vol. 73, 2001, No 4, pp. 1067-1141.10.1103/RevModPhys.73.1067
  13. 13. Herrera, F., M. Lozano. Gradual Distributed Real-Coded Genetic Algorithms. – IEEE Transactions on Evolutionary Computation, Vol. 4, 2000, No 1, pp. 43-63.10.1109/4235.843494
  14. 14. Heywood, P., P. Richmond, S. Maddock. Road Network Simulation Using FLAME GPU. – In: S. Hunold et al., Eds. Proc. of Euro-Par 2015: Parallel Processing Workshops. Euro-Par 2015. Lecture Notes in Computer Science. Vol. 9523. Cham, Springer, 2015, pp. 430-441.
  15. 15. Hong, T., H. Wang. A Dynamic Mutation Genetic Algorithm. – In: Proc. of IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems, Vol. 3, 1996, pp. 2000-2005.
  16. 16. Jameel, F., M. A. Javed, D. T. Ngo. Performance Analysis of Cooperative V2V and V2I Communications Under Correlated Fading. – IEEE Transactions on Intelligent Transportation Systems, Vol. 21, No 8, pp. 3476-3484.10.1109/TITS.2019.2929825
  17. 17. Jurgen, R. V2V/V2I Communications for Improved Road Safety and Efficiency. SAE International, 2012.
  18. 18. Khachatryan, N. K., A. S. Akopov. Model for Organizing Cargo Transportation with an Initial Station of Departure and a Final Station of Cargo Distribution. – Business Informatics, Vol. 1, 2017, No 39, pp. 25-35.10.17323/1998-0663.2017.1.25.35
  19. 19. Kim, K., P. R. Kumar. An MPC-Based Approach to Provable System-Wide Safety and Liveness of Autonomous Ground Traffic. – IEEE Transactions on Automatic Control, Vol. 59, 2014, No 12, pp. 3341-3356.10.1109/TAC.2014.2351911
  20. 20. Kiran, M., P. Richmond, M. Holcombe, C. L. Shawn, D. Worth, C. Greenough. FLAME Simulating Large Populations of Agents on Parallel Platforms. – In: Proc. of 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’10), 2010, pp. 1633-1636.
  21. 21. Müllner, D. Fastcluster: Agglomerative Clustering Routines for R and Python. – Journal of Statistical Software, Vol. 53, 2013, No 9, pp. 1-18.10.18637/jss.v053.i09
  22. 22. Naqvi, F. B., M. Y. Shad, M. S. Khan. A New Logistic Distribution Based Crossover Operator for Real-Coded Genetic Algorithm. – Journal of Statistical Computation and Simulation, Vol. 91, 2021, No 4, pp. 817-835.10.1080/00949655.2020.1832093
  23. 23. Paden, B., M. Čáp, S. Z. Yong, D. Yershov, E. Frazzoli. A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles. – IEEE Transactions on Intelligent Vehicles, Vol. 1, 2016, No 1, pp. 33-55.10.1109/TIV.2016.2578706
  24. 24. Premalatha, M., V. Viswanathan. Course Sequence Recommendation with Course Difficulty Index Using Subset Sum Approximation Algorithms. – Cybernetics and Information Technologies, Vol. 19, 2019, No 3, pp. 25-44.10.2478/cait-2019-0024
  25. 25. Sarma, S. S., K. Sinha, G. Chakraborty, P. Bhabani, B. P. Sinha. Distributed Algorithm for Traffic Dissemination in Manhattan Networks with Optimal Routing-Time. – In: Proc. of Symposium on Applied Computing (SAC’17), 2017, pp. 499-505.10.1145/3019612.3019702
  26. 26. Shiller, Z., Y. Gwo. Dynamic Motion Planning of Autonomous Vehicles. – IEEE Transactions on Robotics and Automation, Vol. 7, 1991, No 2, pp. 241-249.10.1109/70.75906
  27. 27. Thierens, D. Adaptive Mutation Rate Control Schemes in Genetic Algorithms. – In: Proc. of Congress on Evolutionary Computation. CEC’02 (Cat. No 02TH8600), Honolulu, HI, USA, Vol. 1, 2002, pp. 980-985.
  28. 28. Tomas-Gabarron, J., E. Egea-Lopez, J. Garcia-Haro. Vehicular Trajectory Optimization for Cooperative Collision Avoidance at High Speeds. – IEEE Transactions on Intelligent Transportation Systems, Vol. 14, 2013, No 4, pp. 1930-1941.10.1109/TITS.2013.2270009
  29. 29. Toshev, A. Particle Swarm Optimization and Tabu Search Hybrid Algorithm for Flexible Job Shop Scheduling Problem – Analysis of Test Results. – Cybernetics and Information Technologies, Vol. 19, 2019, No 4, pp. 26-44.10.2478/cait-2019-0034
  30. 30. Yuriy, R., L. Viatcheslav. A Novel Multi-Epoch Particle Swarm Optimization Technique. – Cybernetics and Information Technologies, Vol. 18, 2018, No 3, pp. 62-74.10.2478/cait-2018-0039
  31. 31. Zhang, J., H. S. Chung, W. Lo. Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms. – IEEE Transactions on Evolutionary Computation, Vol. 11, 2007, No 3, pp. 326-335.10.1109/TEVC.2006.880727
  32. 32. Zhou, Q., Y. Li. Directed Variation in Evolutionary Strategies. – IEEE Transactions on Evolutionary Computation, Vol. 7, 2003, No 4, 356-366.10.1109/TEVC.2003.812215
DOI: https://doi.org/10.2478/cait-2021-0034 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 127 - 144
Submitted on: May 11, 2021
Accepted on: Jun 15, 2021
Published on: Dec 7, 2021
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2021 Andranik S. Akopov, Levon A. Beklaryan, Armen L. Beklaryan, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.