Viljem Zumer

Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems

We describe an efficient technique for adapting control parameter settings associated with differential evolution (DE). The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters, which are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE. We present an algorithm-a new version of the DE algorithm-for obtaining self-adaptive control parameter settings that show good performance on numerical benchmark problems. The results show that our algorithm with self-adaptive control parameter settings is better than, or at least comparable to, the standard DE algorithm and evolutionary algorithms from literature when considering the quality of the solutions obtained

Self-Adaptive Differential Evolution Algorithm in Constrained Real-Parameter Optimization

Differential Evolution (DE) has been shown to be a powerful evolutionary algorithm for global optimization in many real problems. Self-adaptation has been found to be high beneficial for adjusting control parameters during evolutionary process, especially when done without any user interaction. In this paper we investigate a self-adaptive differential evolution algorithm where more DE strategies are used and control parameters F and CR are self-adapted. The performance of the self-adaptive differential evolution algorithm is evaluated on the set of 24 benchmark functions provided for the CEC2006 special session on constrained real parameter optimization.

High-dimensional real-parameter optimization using Self-Adaptive Differential Evolution algorithm with population size reduction

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 randomly chosen vectors, which are multiplied by the F control parameter (scaling factor) in the mutation operation of DE algorithm. The performance of the jDEdynNP-F algorithm is evaluated on the set of 7 benchmark functions provided for the CECpsila2008 special session on high-dimensional real-parameter optimization.

Dynamic optimization using Self-Adaptive Differential Evolution

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 in dynamic and uncertain environments.

Large Scale Global Optimization using Differential Evolution with self-adaptation and cooperative co-evolution

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 DE is extended by log-normal self-adaptation of its control parameters and combined with cooperative co-evolution as a dimension decomposition mechanism. Experimental results are given for seven high-dimensional test functions proposed for the Special Session on Large Scale Global Optimization at 2008 IEEE World Congress on Computational Intelligence.

LISA: An Interactive Environment for Programming Language Development

The LISA system is an interactive environment for programming language development. From the formal language specifications of a particular programming language LISA produces a language specific environment that includes editors (a language-knowledgable editor and a structured editor), a compiler/interpreter and other graphic tools. The LISA is a set of related tools such as scanner generators, parser generators, compiler generators, graphic tools, editors and conversion tools, which are integrated by well-designed interfaces.

Differential evolution for multiobjective optimization with self adaptation

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 assessed with different performance metrics. Based on these metrics, algorithm strengths and weaknesses are discussed.

Differential Evolution with Self-adaptation and Local Search for Constrained Multiobjective Optimization

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 of the algorithm using CEC 2009 special session and competition on constrained multiobjective optimization test functions is presented. The functions are composed of unconstrained and constrained problems. Their results are assessed using the IGD metric. Based on this metric, algorithm strengths and weaknesses are discussed.

Compiler/interpreter generator system LISA

The paper describes the LISA system which is a generic interactive environment for programming language development. From the formal language specifications of a particular programming language, LISA produces a language specific environment that includes a language-knowledgeable editor, a compiler/interpreter and other graphic tools. The paper focuses on design decisions, implementation issues and tool integration in the system LISA. The main reasons for developing a new compiler/interpreter generator system were: support for incremental language development, support for language design in a visual manner and the portability of the system and the generated environment. LISA is a set of related tools such as scanner generators, parser generators, compiler generators, graphic tools, editor and conversion tools, which are integrated by well designed interfaces. Therefore, it has the advantages of a single system and federated environment. LISA and the generated environment are written in Java which enables high portability to different platforms.

Metaparadigm: A soft and situation oriented MIS design approach

Every-day routine work performed by medical staff can be enormous, thus continuing education, diagnostic assistance, medical research or literature searches remains only an aspiration for them. The appearance of the computer-based information technology has initiated the possibility to significantly ease these routine activities and enable the medical staff to devote more time to enhanced creative work. However, only when medical staff can use computers reliably, effectively, democratically, easily, and in natural, intuitive fashion, medical information system (MIS) will be used enthusiastically and favourably. In that manner special attention must be dedicated to MIS design. The aim of our paper is to introduce the new (M)IS design approach called metaparadigm and show its applicability to MIS design. A metaparadigm is a holistic, participative and systemic approach, incorporating design activities needed to construct both the (M)IS design paradigm and the selected (M)IS. It is our deepest belief that metaparadigms employment can enhance many IS design weaknesses and result in the successful medical information systems design and use.