Predict Energy Charging Points to Electric Vehicles in a Smart City Using a Novel Metaheuristic

Author:

Rivera-Rojo Daniel1,Martinez Carlos1,Almazo Diego1,Caldiño Uzziel1,Ramirez Abdiel1,Tejeda Valdemar2

Affiliation:

1. Autonomous University of Juarez City, Mexico

2. INEEL, Mexico

Abstract

The purpose of this chapter is to understand a multivariable optimization associated with the path of a group of vehicles integrated in an ecological community and determine the optimal route involve speed, storage, and travel resources. Time of charge for determining the cost benefit have partnered with a travel plan associated with the charge point in a smart city, which has as principal basis the orography restriction related with the energy consumed. Although this problem has been studied on several occasions, the literature failed to establish ubiquitous computing for interacting with the various values associated with the achievement of the group of vehicles and their cost-benefit of each member of the community, comparing their individual trips for the group and determining the quantity of energy required for each one. There are several factors that can influence in the achievement of a group trip. For this chapter, the authors propose to use bat algorithm, which has proven to be efficient for the convergence of several issues.

Publisher

IGI Global

Reference14 articles.

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2. Barbucha. (2013). Experimental Study of the Population Parameters Settings in Cooperative Multi-agent System Solving Instances of the VRP. T. Computational Collective Intelligence, 9, 1-28.

3. Evolutionary one-machine scheduling in the context of electric vehicles charging.;M.Carlos;Integrated Computer-Aided Engineering,2019

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