Aleš Zamuda

University of Maribor | UM · Faculty of Electrical Engineering and Computer Science (FERI)

This paper presents a vectorized matrix parameters encoding aspect for an evolutionary computer vision approach to procedural tree modeling. A serialized fixed-size floating-point encoded tree parameter set consists of a set of auxiliary local and other global parameters. The main goal of paper is to lower problem dimensionality needed for encoding...

This paper present short-term combined economic and emission hydrothermal optimization, addressing total fuel costs and emissions minimization. This paper uses the fuel cost function with valve-point effect, which increases the degree of optimization problem difficulty. The optimal balance between the addressed objectives, that conflict with each o...

This paper presents insight into an adaptation and self-adaptation mechanism within differential evolution, covering not only how but moreover – when this mechanism generates new values for control parameters, focusing on the iteration-temporal randomness of the self-adaptive control parameters. In particular, this randomness is controlled by a ran...

This paper presents an approach for tackling constrained underwater glider path planning (UGPP), where the feasible path area is defined as a corridor around the border of an ocean eddy. The objective of the glider here is to sample the oceanographic variables more efficiently while keeping a bounded trajectory. Therefore, we propose a solution bas...

Integrated data analysis (IDA) pipelines---that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring---become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used---increasingly heterogeneous--...

Integrated data analysis pipelines combine rigorous data management and processing, high-performance computing and machine learning tasks. While these systems and operations share many compilation and runtime techniques, data analysts and scientists are currently dealing with multiple systems for each stage of their pipeline. DAPHNE is an open and...

This paper presents tackling of a hard optimization problem of computational linguistics, specifically automatic multi-document text summarization, using grid computing. The main challenge of multi-document summarization is to extract the most relevant and unique information effectively and efficiently from a set of topic-related documents, constra...

This volume constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2019, and 5th International Conference on Fuzzy and Neural Computing, FANCCO 2019, held in Maribor, Slovenia, in July 2019. The 18 full papers presented in this volume were carefully...

Underwater gliders are energy-efficient vehicles that rely on changes in buoyancy in order to convert up and down movement into forward displacement. These vehicles are conceived as multi-sensor platforms, and can be used to collect ocean data for long periods in wide range areas. This endurance is achieved at the cost of low speed, which requires...

The concept of smartness is an essential topic that was only recently extended to rural areas. Although smartness is already incorporated strongly into numerous urban environments, differences between cities and villages prevent direct transfer of the methods and tools used for the smart transformation. To increase the awareness of newly developed...

This paper proposes a new discrete optimization benchmark 100b-Digit, a binary discretized version for the 100-Digit Challenge. The continuous version 100-Digit Challenge utilizing continuous input parameters for a fitness function was suggested for the competitions at 2019 GECCO and 2019 CEC, while this paper proposes an extension, a discrete vers...

This paper describes a competition entry for the "100-Digit Challenge, and Four Other Numerical Optimization Competitions" at The Genetic and Evolutionary Computation Conference (GECCO) 2019, by assessing the function evaluations up to 1e+12, and large population sizes in Distance-based Success History Differential Evolution for the 100-Digit Chall...

The real-world implementation of Underwater Glider Path Planning (UGPP) over the dynamic and changing environment in deep ocean waters requires complex mission planning under very high uncertainties. Such a mission is also influenced to a large extent by remote sensing for forecasting weather models outcomes used to predict spatial currents in deep...

A cooperative model of well-known evolutionary algorithms is proposed and tested on CEC 2019 benchmark suite. The four adaptive algorithms are chosen for this model, namely Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) and three variants of adaptive Differential Evolution. Although the three algorithms use constant population size, th...

Control-flow computer architectures are based on the von Neumann paradigm. They are flexible enough to support the execution of instructions in any order. Each instruction is fetched from the memory before it could be executed. Passing the data from the instruction that produces it to the instruction that requires it is done using registers or memo...

The faithful reproduction and accurate prediction of the phenotypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because o...

This chapter surveys the state-of-the-art in forecasting cryptocurrency value by Sentiment Analysis. Key compounding perspectives of current challenges are addressed, including blockchains, data collection, annotation, and filtering, and sentiment analysis metrics using data streams and cloud platforms. We have explored the domain based on this pro...

This chapter surveys the state-of-the-art in forecasting cryptocurrency value by Sentiment Analysis. Key compounding perspectives of current challenges are addressed, including blockchains, data collection, annotation, and filtering, and sentiment analysis metrics using data streams and cloud platforms. We have explored the domain based on this pro...

This paper proposes a simple, yet effective, modification to scaling factor and crossover rate adaptation in Success-History based Adaptive Differential Evolution (SHADE), which can be used as a framework to all SHADE-based algorithms. The performance impact of the proposed method is shown on the real-parameter single objective optimization (CEC201...

This paper presents an application of a recently well performing evolutionary algorithm for continuous numerical optimization, Success-History Based Adaptive Differential Evolution Algorithm (SHADE) including Linear population size reduction (L-SHADE), to an expert system for underwater glider path planning (UGPP). The proposed algorithm is compare...

This paper provides a taxonomical identification survey of classes in discrete optimization challenges that can be found in the literature including a proposed pipeline for benchmarking, inspired by previous computational optimization competitions. Thereby, a Black-Box Discrete Optimization Benchmarking (BB-DOB) perspective is presented for the [em...

This paper presents a Genetic Algorithm (GA) application to measuring feature importance in machine learning (ML) from a large-scale database. Too many input features may cause over-fitting, therefore a feature selection is desirable. Some ML algorithms have feature selection embedded, e.g., lasso penalized linear regression or random forests. Othe...

This paper presents insights into the proportions between the k-means clusters of successful Differential Evolution (DE), donor generating vectors. This is demonstrated by the high certainty that these proportions are similar - and thereby, that these cluster size proportions regularly appear. A characteristic of these proportions is that they are...

Hybrid societies are self-organizing, collective systems, which are composed of different components, for example, natural and artificial parts (bio-hybrid) or human beings interacting with and through technical systems (socio-technical). Many different disciplines investigate methods and systems closely related to the design of hybrid societies. A...

This paper proposes a lossy image representation where a reference image is approximated by an evolved image, constituted of variable number of triangular brushstrokes. The parameters of each triangle brush are evolved using differential evolution, which self-adapts the triangles to the reference image, and also self-adapts some of the control para...

This paper presents an approach to underwater glider path planning (UGPP), where the population size reduction mechanism is introduced into the differential evolution (DE) meta-heuristic and two types of DE strategies (DE/best and DE/rand) are applied interchangeably. The newly proposed DE instance algorithms using population size reduction on the...

This chapter gives an overview of Differential Evolution (DE), then presents adaptive and self-adaptive mechanisms within the DE algorithm. They can be used in order to make a DE solver more robust, efficient, etc., and to overcome parameter tuning which is usually a time-consuming task needed to be done before the actual optimization process start...

This paper presents an approach where differential evolution is applied to underwater glider path planning. The objective of a glider is to reach a target location and gather research data along its path by propelling itself underwater and returning periodically to the surface. The main hypothesis of this work is that gliders operational capabiliti...

Abstract This paper proposes a lossy image representation where a reference image is approximated by an evolved image, constituted of variable number of triangular brushstrokes. The parameters of each triangle brush are evolved using differential evolution, which self-adapts the triangles to the reference image, and also self-adapts some of the con...

This paper presents a differential evolution (DE) algorithm for real-parameter optimization. The algorithm includes the self-adaptive jDE algorithm with one of its strongest extensions, population reduction, combined with multiple mutation strategies using a structured population. The two mutation strategies used are run dependent on the population...

A new differential evolution algorithm for single objective optimization is presented in this paper. The proposed algorithm uses a self-adaptation mechanism for parameter control, divides its population into more subpopulations, applies more DE strategies, promotes population diversity, and eliminates the individuals that are not changed during som...

Many real-world optimisation problems are of dynamic nature, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. To achieve this, we propose two population-based algorithms for solving dynamic optimisation problems (DOPs) with continuous variables: the self-adaptive differential evolution algorithm...

We propose an environmental framework for simulation and visualization of woody plant forests. A complex application software system develops and animates a spontaneous afforestation process within this environment. The system considers several environmen-tal properties and combines computer animation with artificial life. The main goal of the pres...

This paper presents an innovization design principle for procedural tree model of woody plants (trees) reconstruction by multi-objective optimization. Reconstruction of a parameterized procedural model from imagery is addressed by a multi-objective differential evolution algorithm, which evolves a parametrized procedural model by fitting a set of i...

In this paper we present self-adaptive differential evolution algorithm with a small and varying population size on large scale global optimization. The experimental results obtained by our algorithm on benchmark functions provided for the CEC 2012 competition and special session on Large Scale Global Optimization are presented. The experiments wer...

This paper presents a novel differential evolution algorithm for optimization of state-of-the-art real world industry challenges. The algorithm includes the self-adaptive jDE algorithm with one of its strongest extensions, population reduction, and is now combined with multiple mutation strategies. The two mutation strategies used are run dependent...

This paper presents an approach for reconstruction of procedural three-dimensional models of woody plants (trees). The used procedural tree model operates by recursively computing all building parts of a three-dimensional tree structure by applying a fixed procedure on a given large set of numerically coded input parameters. The parameterized proce...

Differential Evolution (DE) is widely used in solv- ing single objective constrained real-parameter optimization problems. In this paper we present a new version of DE- based algorithm for constrained optimization. A new mutation strategy is also used in the proposed algorithm. The performance of the proposed algorithm is evaluated on the set of 36...

In this paper we present self-adaptive differential evolution algorithm jDElsgo on large scale global optimization. The experimental results obtained by our algorithm on benchmark functions provided for the CEC 2010 competition and special session on Large Scale Global Optimization are presented. The experiments were performed on 20 benchmark funct...

This paper presents a differential evolution (DE) based approach to chess evaluation function tuning. DE with opposition-based optimization is employed and upgraded with a history mechanism to improve the evaluation of individuals and the tuning process. The general idea is based on individual evaluations according to played games through several g...

This paper presents an approach for recognition of procedural three-dimensional models of woody plants (trees). The used procedural tree model operates by building a three-dimensional structure of a tree by applying a fixed procedure on a given set of numerically-coded input parameters. The parameterized procedural model can later be used for compu...

This paper presents differential evolution with self-adaptation and local search for constrained multiobjective optimization algorithm (DECMOSA-SQP), which uses the self-adaptation mechanism from DEMOwSA algorithm presented at CEC 2007 and a SQP local search. The constrained handling mechanism is also incorporated in the new algorithm. Assessment o...

In this paper we investigate a Self-Adaptive Differential Evolution algorithm (jDE) where F and CR control parameters are self-adapted and a multi-population method with aging mechanism is used. The performance of the jDE algorithm is evaluated on the set of benchmark functions provided for the CEC 2009 special session on evolutionary computation i...

This paper presents Differential Evolution with Self-adaptation and Local Search for Constrained Multiobjective Optimization algorithm (DECMOSA-SQP), which uses the self-adaptation mechanism from DEMOwSA algorithm presented at CEC 2007 and a SQP local search. The constrained handling mechanism is also incorporated in the new algorithm. Assessment o...

This chapter describes an algorithm for the tuning of a chess program which is based on Differential Evolution using adaptation and opposition based optimization mechanisms. The mutation control parameter F is adapted according to the deviation of search parameters in each generation. Opposition-based optimization is included in the initialization,...

The main goal of this chapter is to present an analysis of how self-adaptive control parameters are being changed during the current evolutionary process. We present a comparison of two distinct self-adaptive control parameters’ mechanisms, both using Differential Evolution (DE). The first mechanism has recently been proposed in the jDE algorithm,...

In this paper we investigate a self-adaptive differential evolution algorithm ( jDEdynNP-F ) where F and CR control parameters are self-adapted and a population size reduction method is used. Additionally the proposed jDEdynNP-F algorithm uses a mechanism for sign changing of F control parameter with some probability based on the fitness values of...

In this paper, an optimization algorithm is formulated and its performance assessment for large scale global optimization is presented. The proposed algorithm is named DEwSAcc and is based on Differential Evolution (DE) algorithm, which is a floating-point encoding evolutionary algorithm for global optimization over continuous spaces. The original...

This paper presents performance assessment of differential evolution for multiobjective optimization with self adaptation algorithm, which uses the self adaptation mechanism from evolution strategies to adapt F and CR parameters of the candidate creation in DE. Results for several runs on CEC2007 special session test functions are presented and ass...

We present a framework for the simulation of forests, where a complex application system simulates a spontaneous afforestation process. Within this virtual environment, trees can be seen to grow over several centuries. The obtained simulation results are used to animate ecosystem development, where trees struggle for survival. The visualization of...

Najprej podamo zgodovino in razvoj modeliranja in vizualizacije ekosistemov do danes. Nato navedemo uporabljene metode pri simulaciji in opišemo nekatere poglede na vizualizacijo. Za vizualizacijo ekosistemov je bilo potrebno pripraviti vizualno realistične modele rastlin. Pri tem uporabimo leta 2004 pripravljen interaktivni modelirnik in vizualiza...

In this paper we propose an interactive user friendly tool to design tree models. Our tool enables more flexible and rapid construction of procedural models by use of graphs to design local branch parameters as vector data. Our obtained procedural models can also be shaped by placing them in natural environments. Built procedural models can be used...