Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation

Risk Analysis ◽  
2015 ◽  
Vol 35 (9) ◽  
pp. 1690-1705 ◽  
Author(s):  
William M. Kroshl ◽  
Shahram Sarkani ◽  
Thomas A Mazzuchi
Keyword(s):  
Distributed Networks ◽  
Efficient Allocation ◽  
Allocation Of Resources ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Spatially Distributed

scholarly journals Multi-Criteria, Co-Evolutionary Charging Behavior: An Agent-Based Simulation of Urban Electromobility

2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Lennart Adenaw ◽  
Markus Lienkamp
Keyword(s):  
Urban Areas ◽  
City Planning ◽  
User Behavior ◽  
Transport Sector ◽  
Simulation Framework ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Charging Station ◽  
Spatio Temporal

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.

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