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Mayer research group

Evolutionary algorithms for the optimization of optical systems

The development of optical systems generally involves an optimization task in which we seek at finding a set of parameters for which a maximal efficiency is achieved. The complexity of these optimization problems grows exponentially with the number of parameters to determine. Evolutionary algorithms (genetic algorithms, PSO) were developed in our laboratory in order to address these optimization problems more efficiently.


The general idea of a genetic algorithm consists in working with a population of individuals that represent possible solutions to the problem considered. The best individuals are selected. Their parameters are subjected to crossover and mutations in order to determine new individuals for the next generation. This strategy is repeated from generation to generation until the population converges to the global optimum of the problem.


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A multi-objective genetic algorithm was developed for the optimization of systems for which several objectives must be reached. The genetic algorithm can be coupled easily with any external software used for the modeling of the system considered. It will run massively parallel on the supercalculators of the CECI and on the Tier-1, making use of the computational resources of the PTCI technological platform.



New algorithms are currently developed. Amongst them, Particle Swarm Optimization (PSO) is inspired by the dynamics of flocks of birds. It is also used to determine the global optimum of problems.



Optimization of light-emitting diodes (LED), of solar thermal panels, of photovoltaic panels, of metamaterial superabsorbers.


Representative publications

A. Mayer, L. Gaouyat, D. Nicolay, T. Carletti and O. Deparis, Multi-objective genetic algorithm for the optimization of a flat-plate solar thermal collector, Optics Express 22, A1641 (2014)

A. Mayer and A. Bay, Optimization by a genetic algorithm of the light-extraction efficiency of a GaN light-emitting diode, Journal of Optics 17, 025002 (2015)

A. Mayer, J. Muller, A. Herman and O. Deparis, Optimized absorption of solar radiations in nano-structured thin films of crystalline silicon via a genetic algorithm, Proceedings of SPIE 9546, 95461N-01 (2015)

A. Razzaq, A. Mayer, V. Depauw, I. Gordon, A.T. Hajjiah and J. Poortmans, Application of a genetic algorithm in four-terminal perovskite/crystalline-silicon tandem devices, IEEE Journal of Photovoltaics 10, 1689 (2020)

A. Mayer, H. Bi, S. Griesse-Nascimento, B. Hackens, J. Loicq, E. Mazur, O. Deparis and M. Lobet, Genetic-algorithm-aided ultra-broadband perfect absorbers using plasmonic metamaterials, Optics Express 30, 1167 (2022)

N. Roy, Ch. Beauthier and A. Mayer, Setup of a New Adaptive Fuzzy Particle Swarm Optimization Algorithm, IEEE Congress on Evolutionary Computation (2022)



PhotoNVoltaics, Nanophotonics for ultra-thin crystalline silicon photovoltaics, EU Project H2020 FP7-Energy, 2012-2015

Different collaborations on the optimization of optical systems are currently in progress.