Cuckoo search inspired hybridization of the Nelder-Mead simplex algorithm applied to optimization of photovoltaic cells

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10 Citations (Scopus)

Abstract

A new hybridization of the Cuckoo Search (CS) is developed and applied to optimize multi-cell solar systems; namely multi-junction and split spectrum cells. The new approach consists of combining the CS with the Nelder-Mead method. More precisely, instead of using single solutions as nests for the CS, we use the concept of a simplex which is used in the Nelder-Mead algorithm. This makes it possible to use the flip operation introduces in the Nelder-Mead algorithm instead of the Levy flight which is a standard part of the CS. In this way, the hybridized algorithm becomes more robust and less sensitive to parameter tuning which exists in CS. The goal of our work was to optimize the performance of multi-cell solar systems. Although the underlying problem consists of the minimization of a function of a relatively small number of parameters, the difficulty comes from the fact that the evaluation of the function is complex and only a small number of evaluations is possible. In our test, we show that the new method has a better performance when compared to similar but more compex hybridizations of Nelder-Mead algorithm using genetic algorithms or particle swarm optimization on standard benchmark functions. Finally, we show that the new method outperforms some standard meta-heuristics for the problem of interest.

Original languageEnglish
Pages (from-to)961-973
Number of pages13
JournalApplied Mathematics and Information Sciences
Volume10
Issue number3
DOIs
Publication statusPublished - 1 May 2016

Fingerprint

Simplex Algorithm
Photovoltaic cells
Optimization
Solar system
Cell
Solar Cells
Optimise
Lévy Flights
Nest
Particle swarm optimization (PSO)
Parameter Tuning
Evaluation
Flip
Metaheuristics
Tuning
Genetic algorithms
Particle Swarm Optimization
Genetic Algorithm
Benchmark
Standards

Keywords

  • cascaded optimization
  • Cuckoo search
  • Multi-cell solar systems
  • Multi-junction solar cells
  • Nelder-Mead Simplex
  • Split spectrum solar cell system

ASJC Scopus subject areas

  • Applied Mathematics
  • Numerical Analysis
  • Analysis
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

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abstract = "A new hybridization of the Cuckoo Search (CS) is developed and applied to optimize multi-cell solar systems; namely multi-junction and split spectrum cells. The new approach consists of combining the CS with the Nelder-Mead method. More precisely, instead of using single solutions as nests for the CS, we use the concept of a simplex which is used in the Nelder-Mead algorithm. This makes it possible to use the flip operation introduces in the Nelder-Mead algorithm instead of the Levy flight which is a standard part of the CS. In this way, the hybridized algorithm becomes more robust and less sensitive to parameter tuning which exists in CS. The goal of our work was to optimize the performance of multi-cell solar systems. Although the underlying problem consists of the minimization of a function of a relatively small number of parameters, the difficulty comes from the fact that the evaluation of the function is complex and only a small number of evaluations is possible. In our test, we show that the new method has a better performance when compared to similar but more compex hybridizations of Nelder-Mead algorithm using genetic algorithms or particle swarm optimization on standard benchmark functions. Finally, we show that the new method outperforms some standard meta-heuristics for the problem of interest.",
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