Evolutionary Algorithms for Finding Short Addition Chains: Going the Distance

2016 ◽  
pp. 121-137 ◽  
Author(s):  
Stjepan Picek ◽  
Carlos A. Coello Coello ◽  
Domagoj Jakobovic ◽  
Nele Mentens
Keyword(s):  
Evolutionary Algorithms ◽  
Addition Chains

scholarly journals Finding short and implementation-friendly addition chains with evolutionary algorithms

2017 ◽  
Vol 24 (3) ◽  
pp. 457-481 ◽  
Author(s):  
Stjepan Picek ◽  
Carlos A. Coello Coello ◽  
Domagoj Jakobovic ◽  
Nele Mentens
Keyword(s):  
Evolutionary Algorithms ◽  
Addition Chains

Opponent Center-Surround Contrast: Colour to Grey Conversion

2020 ◽  
Vol 2020 (1) ◽  
pp. 105-108
Author(s):  
Ali Alsam
Keyword(s):  
Evolutionary Algorithms ◽  
Three Dimensional ◽  
The State ◽  
Colour Space ◽  
Vision Science ◽  
State Of Art ◽  
Over Time

Vision is the science that informs us about the biological and evolutionary algorithms that our eyes, opticnerves and brains have chosen over time to see. This article is an attempt to solve the problem of colour to grey conversion, by borrowing ideas from vision science. We introduce an algorithm that measures contrast along the opponent colour directions and use the results to combine a three dimensional colour space into a grey. The results indicate that the proposed algorithm competes with the state of art algorithms.

PVT-Biomass-Battery systems optimized with evolutionary algorithms for small and highly shaded environments

2016 ◽  
pp. 568-573
Author(s):  
J.A. Fernández Fernández ◽  
P. González-Rodelas ◽  
E. Alameda-Hernández
Keyword(s):  
Evolutionary Algorithms ◽  
Battery Systems

Applied Process Simulation-Driven Oil and Gas Separation Plant Optimization using Surrogate Modeling and Evolutionary Algorithms

2019 ◽  
Author(s):  
Anders Andreasen
Keyword(s):  
Evolutionary Algorithms ◽  
Gas Separation ◽  
Oil And Gas ◽  
Optimal Solution ◽  
Computer Experiment ◽  
Latin Hypercube Sampling ◽  
Surrogate Models ◽  
Inlet Temperature ◽  
Separation Plant ◽  
Separation Stage

In this article the optimization of a realistic oil and gas separation plant has been studied. Two different fluids are investigated and compared in terms of the optimization potential. Using Design of Computer Experiment (DACE) via Latin Hypercube Sampling (LHS) and rigorous process simulations, surrogate models using Kriging have been established for selected model responses. The surrogate models are used in combination with a variety of different evolutionary algorithms for optimizing the operating profit, mainly by maximizing the recoverable oil production. A total of 10 variables representing pressure and temperature various key places in the separation plant are optimized to maximize the operational profit. The optimization is bounded in the variables and a constraint function is included to ensure that the optimal solution allows export of oil with an RVP < 12 psia. The main finding is that, while a high pressure is preferred in the first separation stage, apparently a single optimal setting for the pressure in downstream separators does not appear to exist. In the second stage separator apparently two different, yet equally optimal, settings are revealed. In the third and final separation stage a correlation between the separator pressure and the applied inlet temperature exists, where different combinations of pressure and temperature yields equally optimal results.<br>

Convergence Analysis and Comparison of Evolutionary Algorithms Based on Relation Model

2011 ◽  
Vol 34 (5) ◽  
pp. 801-811 ◽  
Author(s):  
Han HUANG ◽  
Zhi-Yong LIN ◽  
Zhi-Feng HAO ◽  
Yu-Shan ZHANG ◽  
Xue-Qiang LI
Keyword(s):  
Evolutionary Algorithms ◽  
Convergence Analysis ◽  
Relation Model

Evolutionary Algorithms for Optimizing Cost and QoS on Cloud-based Content Distribution Networks

2019 ◽  
Vol 45 (8) ◽  
pp. 544-556 ◽  
Author(s):  
S. Iturriaga ◽  
S. Nesmachnow ◽  
G. Goñi ◽  
B. Dorronsoro ◽  
A. Tchernykh
Keyword(s):  
Evolutionary Algorithms ◽  
Content Distribution ◽  
Distribution Networks ◽  
Content Distribution Networks

Mother Culture, Meet Mother Nature

2018 ◽  
Author(s):  
Luc Faucher ◽  
Pierre Poirier
Keyword(s):  
Evolutionary Algorithms ◽  
Cultural Change ◽  
Evolutionary Information ◽  
Multiple Forms ◽  
Human Immune System ◽  
Units Of Selection ◽  
Pluralistic Approach ◽  
Human Immune ◽  
Plausible Theory ◽  
Different Time Scales

Research on the adaptive characteristics of the human immune system reveals that evolutionary algorithms are not strictly matters of replication. And research in genomics suggests that there is no a single source of evolutionary information that carries the same content in every environment. A plausible theory of cultural evolution must acknowledge the possibility that multiple selective algorithms are operating at different time-scales, on different units of selection, with different logical structures; but it must explain how different selective processes are interfaced to yield culturally stable phenomena. This paper advances an empirically plausible approach to memetics that recognizes a wider variety of evolutionary algorithms; and it advances a pluralistic approach to cultural change. Finally, it shows that multiple forms of processing, operating at different timescales, on different units of selection, collectively sustain the human capacity to form and use certain types of representations.

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