Optimizing household energy planning in smart cities: A multiobjective approach





smart cities, household energy planning, evolutionary computation, multiobjective optimization, mixed integer programming


This article presents the advances in the design and implementation of a recommendation system for planning the use of household appliances, focused on improving energy efficiency from the point of view of both energy companies and end-users. The system proposes using historical information and data from sensors to define instances of the planning problem considering user preferences, which in turn are proposed to be solved using a multiobjective evolutionary approach, in order to minimize energy consumption and maximize quality of service offered to users. Promising results are reported on realistic instances of the problem, compared with situations where no intelligent energy planning are used (i.e., ‘Bussiness as Usual’ model) and also with a greedy algorithm developed in the framework of the reference project. The proposed evolutionary approach was able to improve up to 29.0% in energy utilization and up to 65,3% in user preferences over the reference methods

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Author Biographies

Sergio Nesmachnow, University of the Republic

Full-time Professor, Faculty of Engineering.

Giovanni Colacurcio, University of the Republic

Engineering student,  Faculty of Engineering.

Diego Gabriel Rossit, National University of the South

Department of Engineering, National University of the South. His field of study is Operations Research and Reverse Logistics. Bahía Blanca Institute of Mathematics, National Council for Scientific and Technical Research CONICET.

Jamal Toutouh, Massachusetts Institute of Technology

Postdoctoral Marie Skłodowska-Curie fellow at MIT (Massachusetts Institute of Technology). He works in ALFA (Anyscale Learning For All) research group at CSAIL (Computer Science and Artificial Intelligence Laboratory). He does research in Co-/Evolutionary Algorithms and Deep Learning to address Cybersecurity and Smart Citiy problems.

Francisco Luna, University of Málaga

Researcher at the Department of Computer Sciences and Languages of the University of Málaga.


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How to Cite

Nesmachnow, S., Colacurcio, G., Rossit, D. G., Toutouh, J., & Luna, F. (2020). Optimizing household energy planning in smart cities: A multiobjective approach. Revista Facultad De Ingeniería Universidad De Antioquia, (101), 8–19. https://doi.org/10.17533/udea.redin.20200587

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