Josef Tvrdík

Competitive differential evolution applied to CEC 2013 problems

A variant of adaptive differential evolution (DE) with twelve competing strategies was applied to the set of benchmark problems proposed for the CEC 2013 competition. Competitive adaptation of DE strategies and parameter settings avoids tuning of most control-parameter values because only the size of population must be set by the user of the algorithm. The experimental results showed acceptable reliability of the search first of all in the problems with unrotated objective functions of smaller dimension. The possible cause of unreliability of the algorithm in the rotated functions is analyzed.

Adaptive Variants of Differential Evolution: Towards Control-Parameter-Free Optimizers

Seven up-to-date adaptive variants of differential evolution were compared in six benchmark problems of two levels of dimension (D = 30 and D = 100). The opposition-based optimization was also implemented to each adaptive variant and compared in experiments. It was found that all the algorithms perform very reliably in the problems of D = 30, whereas their reliability rate in the problems of D = 100 differs substantially among the test problems. Only two algorithms (JADE and b6e6rl variant of competitive DE) operate with acceptable reliability in all the problems. Considering the computational costs, the rank of the algorithms is different in various problems. When the average performance over all the problems is taken into account, JADE was the most efficient and b6e6rl the most reliable. The implementation of opposition-based optimization into adaptive variants of differential evolution does not increase the reliability and its positive influence on the efficiency is rare. Based on the results, recommendations to application of adaptive algorithms are formed and the source code of the algorithms is available online.

Combination of water immersion and carbon dioxide insufflation for minimal sedation colonoscopy: a prospective, randomized, single-center trial.

Objective Water immersion insertion and carbon dioxide (CO2) insufflation, as alternative colonoscopic techniques, are able to reduce patient discomfort during and after the procedure. We assessed whether the combination of water immersion and CO2 insufflation is superior in efficacy and patient comfort to other colonoscopic techniques. Methods In a prospective, randomized study, a total of 420 patients were randomized to either water immersion insertion and CO2 insufflation during withdrawal (water/CO2), water insertion and air insufflation during withdrawal (water/air), CO2 insufflation during both insertion and withdrawal (CO2/CO2), or air insufflation during both insertion and withdrawal (air/air). The main outcome was the success of minimal sedation colonoscopy, which was defined as reaching the cecum without switching to another insertion method and without additional sedation beyond the initial 2 mg of midazolam. Patient comfort during and after the procedure was assessed. Results A total of 404 patients were analyzed. The success rate of minimal sedation colonoscopy in the water insertion arm (water/CO2 and water/air) was 97% compared with 83.3% in the gas insertion arm (CO2/CO2 and air/air; P<0.0001). Intraprocedural pain and bloating were significantly lower in the water/CO2 group than in all other groups. Patient discomfort in the water/CO2 group during 24 h after the procedure was comparable with that in the CO2/CO2 group and significantly lower than that in the air groups (water/air and air/air). No complications were recorded during the study. Conclusion The combination of water immersion and CO2 insufflation appears to be an effective and safe method for minimal sedation colonoscopy. Overall patient discomfort was significantly reduced compared with that in other techniques.

Adaptive differential evolution and exponential crossover

Several adaptive variants of differential evolution are described and compared in two sets of benchmark problems. The influence of exponential crossover on efficiency of the search is studied. The use of both types of crossover together makes the algorithms more robust. Such algorithms are convenient for the real-world problems, where we need an adaptive algorithm applicable without time-wasting parameter tuning.

The controlled random search algorithm in optimizing regression models

This paper deals with the problems of controlled random search algorithms (CRS algorithms) and their use in regression analysis. A modified CRS algorithm of Price is described, which is more effective when compared with the original algorithm in optimizing regression models, first non-linear ones. The principal modification consists in randomizing the search for the next trial points. Some results of testing the algorithm, using both real and modeled data, are given to illustrate its possibilities when estimating the parameters of non-linear regression models.

Controlled restart in differential evolution applied to CEC2014 benchmark functions

A controlled restart in differential evolution (DE) is proposed. The conditions of restart are derived from the difference of maximum and minimum values of the objective function and the estimated maximum distance among the points in the current population. The restart is applied in a competitive-adaptation variant of DE. This DE algorithm with the controlled restart is used in the solution of the benchmark problems defined for the CEC 2014 competition. Two control parameters of restart are set up intuitively. The population size, which is the only control parameter of competitive-adaptation variant of DE, is set up to the values based on a short preliminary experimentation.

Persistence with first line anticholinergic medication in treatment-naïve overactive bladder patients

Abstract Objective. The aim of this study was to evaluate the persistence of first line anticholinergic medication use by patients with overactive bladder (OAB). Data from a hospital outpatient database were matched with information obtained by a telephone survey of patients to determine which patients discontinued use of anticholinergic medication and to identify the reasons underlying discontinuation. Material and methods. The study group included 377 OAB patients (52 men, 325 women) with a mean age of 60.29 ± 13.84 years. In total, 189 patients (50.1%) were treated with trospium (median dose 27.86 ± 12.73 mg), 41 patients (10.9%) with propiverine (28.17 ± 4.97 mg), nine patients (2.4%) with extended-release tolterodine (4.0 ± 0 mg), 48 patients (12.7%) with solifenacin (5.94 ± 1.97 mg) and 90 patients (23.9%) with fesoterodine (6.09 ± 2.01 mg). Results. The median time for persistence with the first line anticholinergic treatment was 6.53 ± 3.84 months. Persistence was significantly higher in patients treated with anticholinergic medication with an extended-release formulation than in patients treated with immediate-release anticholinergics. The most common reasons for termination of treatment were healing/resolution of symptoms (35.9%), low effectiveness (30.9%) and side-effects (23.7%). Conclusions. More than half of the OAB patients were not satisfied with their first line treatment. Other treatment options should be sought, such as changing the medication or dosage, or possibly combining treatments.

Adaptive population-based search: Application to estimation of nonlinear regression parameters

Algorithms for the estimation of nonlinear regression parameters are considered. Adaptive population-based search algorithms are proposed and implemented in deriving reliable estimates at a reasonable time with default setting of their controlling parameters. The algorithms are tested on the NIST collection of data sets containing 27 nonlinear regression tasks of various level of difficulty. The experimental results show that both algorithms with competing heuristics are significantly more reliable as compared with the algorithm based on Levenberg-Marquardt optimizing procedure.

Hybrid differential evolution algorithm for optimal clustering

Graphical abstractDisplay Omitted HighlightsNew hybrid algorithm for optimal clustering is proposed.Algorithm combines differential evolution with k-means.Efficient heuristic for rearrangement of cluster centers is proposed.Hybrid algorithm with center rearrangement is much faster than other variants. The problem of optimal non-hierarchical clustering is addressed. A new algorithm combining differential evolution and k-means is proposed and tested on eight well-known real-world data sets. Two criteria (clustering validity indexes), namely TRW and VCR, were used in the optimization of classification. The classification of objects to be optimized is encoded by the cluster centers in differential evolution (DE) algorithm. It induced the problem of rearrangement of centers in the population to ensure an efficient search via application of evolutionary operators. A new efficient heuristic for this rearrangement was also proposed. The plain DE variants with and without the rearrangement were compared with corresponding hybrid k-means variants. The experimental results showed that hybrid variants with k-means algorithm are essentially more efficient than the non-hybrid ones. Compared to a standard k-means algorithm with restart, the new hybrid algorithm was found more reliable and more efficient, especially in difficult tasks. The results for TRW and VCR criterion were compared. Both criteria provided the same optimal partitions and no significant differences were found in efficiency of the algorithms using these criteria.

Differential evolution with rotation-invariant mutation and competing-strategies adaptation

A new variant of the adaptive differential evolution algorithm was proposed and tested experimentally on the CEC 2014 test suite. In the new variant, the adaptation is based on the competition of several strategies. A part of strategies in the pool uses the rotation-invariant current-to-pbest mutation in the novel algorithm. The aim of the experimental comparison was to find whether the presence of the rotation-invariant strategy is able to improve the efficiency of the differential evolution algorithm, especially in problems with rotated objective functions. The results of the experiments showed that the new variant performed well in a few of the test problems, while no apparent benefit was observed in the majority of the benchmark problems.