On relation between swarm and evolutionary dynamics and complex networks

This paper is an introduction to a novel method for visualizing the dynamics of evolutionary algorithms in the form of networks. The whole idea is based on the obvious similarity between interactions between individuals in a swarm and evolutionary algorithms and for example, users of social networks, linking between web pages, etc. In this paper, two completely different areas of research are merged: (complex) networks and evolutionary computation. As already mentioned, interactions among the individuals in a swarm and evolutionary algorithms can be considered like user interactions in social networks or just people in society. This induces hypothesis whether interactions inside of EAs can be taken like interactions in society or swarm colonies. The analogy between individuals in populations in an arbitrary evolutionary algorithm and vertices of a network is discussed, as well as between edges in a network and communication between individuals in a population. © Springer Nature Switzerland AG 2019

How unconventional chaotic pseudo-random generators influence population diversity in differential evolution

This research focuses on the modern hybridization of the discrete chaotic dynamics and the evolutionary computation. It is aimed at the influence of chaotic sequences on the population diversity as well as at the algorithm performance of the simple parameter adaptive Differential Evolution (DE) strategy: jDE. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the chaotic pseudo-random number generators. The population diversity and jDE convergence are recorded for 15 test functions from the CEC 2015 benchmark set in 30D. © Springer International Publishing AG, part of Springer Nature 2018.2018/177; IC406; MSMT-7778/2014, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; LO1303, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; 710577, Horizon 2020; CA15140; IGA/CebiaTech/2018/003; CZ.1.05/2.1.00/03.0089, FEDER, European Regional Development FundMinistry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST ActionEuropean Cooperation in Science and Technology (COST) [CA15140, IC406]; SGS [2018/177]; VSB-TUO; EU's Horizon 2020 research and innovation programme [710577

Introducing the run support strategy for the bison algorithm

Many state-of-the-art optimization algorithms stand against the threat of premature convergence. While some metaheuristics try to avoid it by increasing the diversity in various ways, the Bison Algorithm faces this problem by guaranteeing stable exploitation – exploration ratio throughout the whole optimization process. Still, it is important to ensure, that the newly discovered solutions can affect the overall optimization process. In this paper, we propose a new Run Support Strategy for the Bison Algorithm, that should enhance the utilization of newly discovered solutions, and should be suitable for both continuous and discrete optimization. © Springer Nature Switzerland AG 2020

Randomization of individuals selection in differential evolution

This research deals with the hybridization of two computational intelligence fields, which are the chaos theory and evolutionary algorithms. Experiments are focused on the extensive investigation on the different randomization schemes for selection of individuals in differential evolution algorithm (DE). This research is focused on the hypothesis whether the different distribution of different pseudo-random numbers or the similar distribution additionally enhanced with hidden complex chaotic dynamics providing the unique sequencing are more beneficial to the heuristic performance. This paper investigates the utilization of the two-dimensional discrete chaotic systems, which are Burgers and Lozi maps, as the chaotic pseudo-random number generators (CPRNGs) embedded into the DE. Through the utilization of either chaotic systems or equal identified pseudo-random number distribution, it is possible to entirely keep or remove the hidden complex chaotic dynamics from the generated pseudo random data series. This research utilizes set of 4 selected simple benchmark functions, and five different randomizations schemes; further results are compared against canonical DE. © Springer Nature Switzerland AG 2019

Chaos powered grammatical evolution

In this paper we discuss alternative nonrandom generators for symbolic regression algorithms and compare its variants powered by classical pseudo-random number generator and chaotic systems. Experimental data from previous experiments reported for genetic programming and analytical programming is used. The selected algorithms are differential evolution and SOMA. Particle swarm, simulated annealing and evolutionary strategies are in process of investigation. All of them are mutually used in scheme Master-Slave meta-evolution for final complex structure fitting and its parameter estimation.Agency of the Czech Republic-GACR [P103/13/08195S]; SGS [SP2014/159]; VSB-Technical University of Ostrava, Czech Republic; European Regional Development Fund [CZ.1.05/2.1.00/03.0089

Non-invasive and invasive diagnoses of aspergillosis in a rat model by mass spectrometry

Invasive pulmonary aspergillosis results in 450,000 deaths per year and complicates cancer chemotherapy, transplantations and the treatment of other immunosuppressed patients. Using a rat model of experimental aspergillosis, the fungal siderophores ferricrocin and triacetylfusarinine C were identified as markers of aspergillosis and quantified in urine, serum and lung tissues. Biomarkers were analyzed by matrix-assisted laser desorption ionization (MALDI) and electrospray ionization mass spectrometry using a 12T SolariX Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. The limits of detection of the ferri-forms of triacetylfusarinine C and ferricrocin in the rat serum were 0.28 and 0.36 ng/mL, respectively. In the rat urine the respective limits of detection achieved 0.02 and 0.03 ng/mL. In the sera of infected animals, triacetylfusarinine C was not detected but ferricrocin concentration fluctuated in the 3-32 ng/mL range. Notably, the mean concentrations of triacetylfusarinine C and ferricrocin in the rat urine were 0.37 and 0.63 μg/mL, respectively. The MALDI FTICR mass spectrometry imaging illustrated the actual microbial ferricrocin distribution in the lung tissues and resolved the false-positive results obtained by the light microscopy and histological staining. Ferricrocin and triacetylfusarinine C detection in urine represents an innovative non-invasive indication of Aspergillus infection in a host

The simulation study of recursive ABC method for warehouse management

The paper deals with a complex warehouse simulation to accomplish a competent solution. It belongs to a group of articles where we are constantly trying to explore the use of warehouses and add further extensions. Greater consideration is concentrated on the use of recursive ABC method for warehouse management in extended concept. The aspiration of the simulation study is to prove whether recursive ABC method returns additional benefits in optimizing the warehouse in this case at a warehouse of different sizes. The complete simulation and the mathematical calculations are accomplished in the Witness Lanner simulation program. The goal of this simulation study is to observe a better solution using recursive ABC method in each part of the model multiple times. Both warehouses are established first on the ABC method, secondary are based on the recursion method. The focus is on two very different layouts of warehouses. Further, the simulation study contributes to propositions that can enhance warehouse management and thus decrease costs. The Witness simulation environment is used for modelling and experimenting. All mathematical computations and simulations are evaluated and measured, as well as all settings of input and output values. Description of the proposed simulation experiments and evaluation of achieved results are presented in tables. © 2019, Springer Nature Switzerland AG.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT7778/2014)]; European Regional Development Fund under the project CEBIATech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/FAI/2017/003

On the tuning of complex dynamics embedded into differential evolution

This research deals with the hybridization of the two soft-computing fields, which are chaos theory and evolutionary computation. This paper aims on the experimental investigations on the chaos-driven evolutionary algorithm Differential Evolution (DE) concept. This research represents the continuation of the satisfactory results obtained by means of chaos embedded (driven) DE, which utilizes the chaotic dynamics in the place of pseudorandom number generators This work is aimed at the tuning of the complex chaotic dynamics directly injected into the DE. To be more precise, this research investigates the influence of different parameter settings for discrete chaotic systems to the performance of DE. Repeated simulations were performed on the IEEE CEC 13 benchmark functions set in dimension of 30. Finally, the obtained results are compared with canonical DE and jDE. © Springer International Publishing Switzerland 2015.MSMT-7778/2014, NPU, Northwestern Polytechnical Universit

Population diversity analysis in adaptive differential evolution variants with unconventional randomization schemes

This research represents a detailed insight into the modern and popular hybridization of unconventional quasiperiodic/chaotic sequences and evolutionary computation. It is aimed at the influence of different randomization schemes on the population diversity, thus on the performance, of two selected adaptive Differential Evolution (DE) variants. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo-random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the unconventional chaotic pseudo-random number generators. The population diversity is recorded for 15 test functions from the CEC 2015 benchmark set in 10D. © 2019, Springer Nature Switzerland AG.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2019/002]; COST (European Cooperation in Science & Technology) under Action (ImAppNIO) [CA15140]; COST (European Cooperation in Science & Technology) under Action (cHiPSet) [IC1406]; VSB-Technical University of Ostrava [SGS 2019/137