The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Differential evolution (DE) is a promising algorithm for continuous optimization. Its two parameters, CR and F, have great effect on the algorithm performance. In recent years many DE algorithms with parameter control mechanisms were proposed. In this paper we propose a taxonomy to classify these algorithms according to the number of candidate parameter values, the number of parameter values used...
Recent research has shown for different particle swarm optimization algorithms that unconstrained particles exhibit roaming behavior in that particles leave the boundaries of the search space very early during the search [1], [2]. This results in fruitless search of infeasible space, and will result in particles finding infeasible solutions if better solutions exist outside of the boundaries of the...
Differential Evolution (DE) has been demonstrated to be an effective algorithm for global optimization. Theoretical and empirical analysis of the global convergence of DE is believed to be very significant. However, not much research has so far been devoted to theoretically analyzing the convergence properties of DE, especially with a finite population. This paper proves that the canonical differential...
Estimation of population characteristics for sub-national geographically defined domains such as regions, states, districts and local government areas can be considered one of the important issues of statistical surveys. A general method in small area estimation (SAE) is the use of linear mixed models with area specific random effects to account for between areas variation beyond that explained by...
Evolutionary algorithms are a popular choice for solving multi-disciplinary optimization problems as they are simple to use and are widely applicable. However, such algorithms require numerous function evaluations prior to its convergence. In the context of constrained optimization (i.e. a vast majority of real life problems), such algorithms use some sort of constraint violation (CV) measure to rank...
Dynamic Economic Dispatch(DED) is a very well known non-linear constrained problem with non convex characteristics due to valve-point effects. Several classical approaches have been employed to find the optimal scheduling of generation units of which Differential Evolution(DE), Particle Swarm Optimization( PSO) and their variants are mostly successful, even with large number of generation units. Differential...
This paper proposes a novel implementation of micro-Differential Evolution (μDE) that incorporates within the DE scheme an extra search move that attempts to improve the best solution by perturbing it along the axes. These extra moves complement the DE search logic and allows the exploration of the decision space from an alternative perspective. In addition, these extra moves at subsequent activations...
In this paper we show how relative characteristics of individuals in context of their population can be used to customize and guide the search process in Differential Evolution, which is a state-of-the art real-parameter global optimization algorithm. Analysis of exploitation phase of the search process shows that probability of creating an offspring, which outperforms its parent and can hence enter...
Differential Evolution is a stochastic, population-based optimization algorithm that has gained wide popularity these days for solving multi-modal, non-smooth, non-convex, and ill-behaved optimization problems. In this research article, we propose a restrictive mutation strategy that helps to probabilistically select individuals for mutation based on the information conveyed by neighboring individuals...
This paper presents an empirical approach for the performance tuning of Java EE application servers (ASs) using a multi-objective differential evolution algorithm. It features multi-objective black-box optimization of selected AS's configuration parameters. The proposed approach is used for performance tuning of the AS GlassFish and Java EE test application DayTrader. The obtained results improve...
Differential Evolution is an efficient and powerful population-based stochastic search technique that has been applied mainly to optimization problems over continuous spaces. Despite its potential only a few researchers have recently explored its use in the machine learning domain, specifically for clustering problems. In this paper, we investigate the use of differential evolution for classification...
This paper proposes a systematic method to identify the parameters of the LuGre friction model and tune the feedback corresponding compensator. Because of the non linearity of the model, those tasks are difficult and often need lots of time-consuming experiments which are not always compatible with industrial constraints. In this work, the use of a Differential Evolution algorithm (belonging to the...
This paper describes a synthesis method for null insertion in linear antenna array geometries by using newly proposed ensemble differential evolution (DE) algorithm. The given ensemble DE algorithm uses the advantages of several types of DE algorithms, and fuses them within a single algorithm. In the application, the algorithm searches for the minimization of the difference between the produced radiation...
In this paper, an optimal Discrete Wavelet Transform-Singular Value Decomposition (DWT-SVD) based image watermarking scheme using differential evolution (DE) algorithm is presented. Three-level DWT is applied to the cover image to transform it into sub-bands of different frequencies and then apply the SVD to each sub-band of third level. After applying one-level DWT to the watermark, singular values...
This paper presents a random key Differential Evolution algorithm to find the optimal box type sequence and the layer type orientation for a three dimensional single container loading problem. The packing algorithm is based on the layer building approach which groups the boxes of the same type to create layers that are packed into empty spaces in the container. The spaces where layers are represented...
Over the last few years, Differential Evolution (DE) algorithms have shown brilliant performance in solving a wide variety of complex optimization problems. However, there is no guarantee that these algorithms will not be trapped in local optima for some problems. In this paper, a DE algorithm is proposed that uses a new mechanism to escape from local optima, during the evolution process by injecting...
The dissipative Lozi chaotic map is embedded in the Enhanced Differential Evolution (EDE) algorithm, as a pseudorandom generator. This novel chaotic based algorithm is applied to the constraint based Lot-Streaming Flowshop scheduling problem. Two new and unique data sets generated using the Lozi and Dissipative maps are used to compare the chaos embedded EDE (EDEC) and the generic EDE utilising the...
Optimization in a dynamic environment is a real challenge owing to the multimodality, high complexity, and ruggedness of the functions involved. Tracking the global optima in such a dynamically changing landscape is called Dynamic Optimization Problem(DOP). This paper aims at modifying the popular DOP handling technique Dynamic Differential Evolution( DynDE) by introducing a unique scheme named Difference...
Many optimization problems possess multiple global solutions or comparably fit local solutions. These multimodal optimization problems require the identification of not just one global optimal, but also multiple compatible solutions. Differential Evolution (DE) has been demonstrated to be highly effective for solving single-objective unimodal problems, but its loss of diversity over the course of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.