[00168] Applications of evolutionary algorithms in differential equation models
Session Time & Room : 1C (Aug.21, 13:20-15:00) @E811
Type : Proposal of Minisymposium
Abstract : Evolutionary algorithms (EAs) have been at the forefront of computational science in solving optimization problems arising from science and engineering. EAs gained popularity because of their capability to obtain global minimizers of non-smooth objective functions. In this minisymposium, we explore the applications of EAs in solving optimization problems arising from differential equation models. Recent techniques in unconstrained, constrained, and multi-objective EAs will be presented along with applications in parameter estimation and control of infectious disease models, medical image reconstruction in electrical impedance tomography, optimal placement of sensors of tsunami sensors, and other applications in engineering.
[03121] Spherical search with multi-operator differential evolution for constrained optimization problems
Format : Talk at Waseda University
Author(s) :
Renier Mendoza (Institute of Mathematics, University of the Philippines Diliman)
Jongmin Lee (Konkuk University)
Victoria May Paguio Mendoza (University of the Philippines Diliman)
Eunok Jung (Konkuk University)
Abstract : We propose a new method, SASS-MODE, for solving constrained optimization problems by combining the self-adaptive spherical search (SASS) with the improved multi-operator differential evolution (IMODE). We adapted IMODE to handle constraints with three modifications and tested our method on 57 benchmark problems and an optimal control problem from an infectious disease model. SASS-MODE outperforms recent algorithms and achieves state-of-the-art results.
[02925] Minimizing infections and intervention cost: multi-objective approach with user-friendly dashboard
Format : Talk at Waseda University
Author(s) :
Jongmin Lee (Department of Mathematics, Konkuk University)
Renier Mendoza (Institute of Mathematics, University of the Philippines Diliman)
Victoria May P. Mendoza (Institute of Mathematics, University of the Philippines Diliman)
Eunok Jung (Department of Mathematics, Konkuk University)
Abstract : During the COVID-19 pandemic, the world faces the challenge of reducing the number of infections while simultaneously minimizing the cost of intervention policies. This study proposes a deterministic model and multi-objective optimization approach that balances these conflicting objectives. Metropolis-Hastings algorithm estimated parameters, and the genetic algorithm found multi-objective optimization solutions. From Pareto solutions, users can select the most suitable solution by considering economic-related parameters. Additionally, we develop a user-friendly, web-based dashboard for ease of use.
[02755] Comparative Study of Heuristic Algorithms for Electrical Impedance Tomography
Format : Talk at Waseda University
Author(s) :
Arrianne Crystal Velasco (Institute of Mathematics, University of the Philippines Diliman)
Renier Mendoza (Institute of Mathematics, University of the Philippines Diliman)
Marion Darbas (LAGA CNRS UMR 7539, University Sorbonne Paris Nord)
Monica Bacon (Institute of Mathematics, University of the Philippines Diliman)
Johm Cedrick de Leon (Institute of Mathematics, University of the Philippines Diliman)
Abstract : Based on electrical measurements from electrodes placed around the boundary of a body, electrical impedance tomography (EIT) is an imaging procedure that recovers the spatial distribution of the conductivities in the interior of a body. This work presents a study of the applicability of six heuristic algorithms for the EIT image reconstruction problem.
[03163] Bi-objective optimization considering bed capacity and timing of interventions
Format : Talk at Waseda University
Author(s) :
Victoria May Paguio Mendoza (University of the Philippines Diliman)
Renier Mendoza (Institute of Mathematics, University of the Philippines Diliman)
Youngsuk Ko (Department of mathematics, Konkuk university)
Jongmin Lee (Konkuk University)
Eunok Jung (Konkuk University)
Abstract : Without vaccines and medicine, non-pharmaceutical interventions are the main strategy for controlling the spread of diseases. A bi-objective optimization problem is formulated that allows for the easing of restrictions at an earlier time and minimizes the number of additional beds ensuring sufficient capacity in healthcare facilities. We utilize a compartmental model that distinguishes mild from severe cases. The multiple optimal solutions of the bi-objective problem offer trade-off solutions that can be useful decision-support tools.
