@inproceedings{db4ab71006734d32bfb80a75c176b818,
title = "Optimal Wireless Meter Deployment Using Evolutionary Algorithms",
abstract = "Utility companies use smart wireless meters to automate the collection of meter readings. This requires them to design and deploy a wireless meter network where each meter is connected to a central Data Concentrator Unit (DCU), which is then connected to the control centre of the company. In this paper we investigate the problem of wireless network meter deployment by means of evolutionary algorithms. We model the deployment problem as an evolutionary optimization problem, explore two different encoding schemes for the objective function, and test 4 different algorithms against 5 typical setups of the network in different areas. Our results show that Simulated Annealing (SA) is the best performing algorithm for the tested instances of the problem and has better reliability against the other compared algorithms The devised models and the algorithm have been built into a tool that is being used in a real-world scenario.",
keywords = "Estimation of Distribution Algorithm, Genetic Algorithm, Optimization, Simulated Annealing, Wireless Meter Network Planning",
author = "Siddhartha Shakya and Kin Poon and Ahmed Suliman and Alia Aljasmi and Huda Goian and Ahoud Barzaiq",
note = "Publisher Copyright: {\textcopyright} 2024 by SCITEPRESS – Science and Technology Publications, Lda.; 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2024 ; Conference date: 10-07-2024 Through 12-07-2024",
year = "2024",
doi = "10.5220/0012791900003758",
language = "British English",
series = "Proceedings of the International Conference on Simulation and Modeling Methodologies, Technologies and Applications",
pages = "332--339",
editor = "\{De Rango\}, Floriano and Frank Werner and Gerd Wagner",
booktitle = "Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2024",
}