Integration of Genetic Algorithm and Monte Carlo Simulation for System Design and Cost Allocation Optimization in Complex Network

Integration of Genetic Algorithm and Monte Carlo Simulation for System Design and Cost Allocation Optimization in Complex Network

Baladeh, Aliakbar Eslami (MAPNA Group, Tehran)
Khakzad, N. (TU Delft Safety and Security Science)

2019

Complex networks play a vital role in reliability analysis of real-world applications, demanding for precise and accurate analysis methods for optimal allocations of cost and reliability. Since the configuration of a system may change with every feasible solution of cost allocation optimization equation, finding the best arrangement of the system can become very challenging. This paper presents a novel methodology by combining Genetic Algorithm (GA) and Monte Carlo (MC) simulation approaches to simultaneously optimize cost allocation and system configuration in complex network. GA is used to generate configuration-cost pairs while MC is used to evaluate the reliability of the system for each pair. The application of the developed methodology is demonstrated for power grids as an example of critical complex networks. The results show that the proposed methodology can be readily used in practice.

complex networks
cost allocation
genetic algorithm
Monte Carlo simulation
optimization
Reliability

http://resolver.tudelft.nl/uuid:cbde185b-7612-4915-b13f-47adb099b0b2

https://doi.org/10.1109/ICSRS.2018.8688846

Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NY, USA

978-1-7281-0238-2

Proceedings - 2018 3rd International Conference on System Reliability and Safety, ICSRS 2018

3rd International Conference on System Reliability and Safety, ICSRS 2018, 2018-11-24 → 2018-11-26, Barcelona, Spain

Institutional Repository

conference paper

© 2019 Aliakbar Eslami Baladeh, N. Khakzad