Evolutionary bi-objective optimization for the electric vehicle charging stand infrastructure problem

Author:

Armas Rolando1,Aguirre Hernan2,Orellana Daniel3

Affiliation:

1. Yachay Tech University, Urcuqui, Ecuador

2. Shinshu University, Nagano, Japan

3. Universidad de Cuenca, Cuenca, Ecuador

Publisher

ACM

Reference26 articles.

1. Horni A., Nagel K., and Axhausen K.W . 2016 . The Multi-Agent Transport Simulation MATSim . London: Ubiquity Press. , London . Horni A., Nagel K., and Axhausen K.W. 2016. The Multi-Agent Transport Simulation MATSim. London: Ubiquity Press., London.

2. H. Aguirre , A. Oyama , and K. Tanaka . 2013. Adaptive ∊-Sampling and ∊-Hood for Evolutionary Many-Objective Optimization . In Evolutionary Multi-Criterion Optimization (Lecture Notes in Computer Science , Vol. 7811). Springer Berlin Heidelberg, 322-- 336 . H. Aguirre, A. Oyama, and K. Tanaka. 2013. Adaptive ∊-Sampling and ∊-Hood for Evolutionary Many-Objective Optimization. In Evolutionary Multi-Criterion Optimization (Lecture Notes in Computer Science, Vol. 7811). Springer Berlin Heidelberg, 322--336.

3. Optimization and Visualization in Many-Objective Space Trajectory Design

4. H. Aguirre , Y. Yazawa , A. Oyama , and K. Tanaka . 2014. Extending A∊S∊H from Many-objective to Multi-objective Optimization . In Simulated Evolution and Learning (Lecture Notes in Computer Science , Vol. 8886). Springer International Publishing, Cham, 239-- 250 . H. Aguirre, Y. Yazawa, A. Oyama, and K. Tanaka. 2014. Extending A∊S∊H from Many-objective to Multi-objective Optimization. In Simulated Evolution and Learning (Lecture Notes in Computer Science, Vol. 8886). Springer International Publishing, Cham, 239--250.

5. Evolutionary design optimization of traffic signals applied to Quito city

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