Investigating Smart Sampling as a population initialization method for Differential Evolution in continuous problems

Recently, researches have shown that the performance of metaheuristics can be affected by population initialization. Opposition-based Differential Evolution (ODE), Quasi-Oppositional Differential Evolution (QODE), and Uniform-Quasi-Opposition Differential Evolution (UQODE) are three state-of-the-art methods that improve the performance of the Differential Evolution algorithm based on population initialization and different search strategies. In a different approach to achieve similar results, this paper presents a technique to discover promising regions in a continuous search-space of an optimization problem. Using machine-learning techniques, the algorithm named Smart Sampling (SS) finds regions with high possibility of containing a global optimum. Next, a metaheuristic can be initialized inside each region to find that optimum. SS and DE were combined (originating the SSDE algorithm) to evaluate our approach, and experiments were conducted in the same set of benchmark functions used by ODE, QODE and UQODE authors. Results have shown that the total number of function evaluations required by DE to reach the global optimum can be significantly reduced and that the success rate improves if SS is employed first. Such results are also in consonance with results from the literature, stating the importance of an adequate starting population. Moreover, SS presents better efficacy to find initial populations of superior quality when compared to the other three algorithms that employ oppositional learning. Finally and most important, the SS performance in finding promising regions is independent of the employed metaheuristic with which SS is combined, making SS suitable to improve the performance of a large variety of optimization techniques. (C) 2012 Elsevier Inc. All rights reserved.

Comparative study of classic friction among different archwire ligation systems

OBJECTIVE: To describe and compare three alternative methods for controlling classical friction: Self-ligating brackets (SLB), special brackets (SB) and special elastomeric ligatures (SEB). METHODS: The study compared Damon MX, Smart Clip, In-Ovation and Easy Clip self-ligating bracket systems, the special Synergy brackets and Morelli's twin bracket with special 8-shaped elastomeric ligatures. New and used Morelli brackets with new and used elastomeric ligatures were used as control. All brackets had 0.022 x 0.028-in slots. 0.014-in nickel-titanium and stainless steel 0.019 x 0.025-in wires were tied to first premolar steel brackets using each archwire ligation method and pulled by an Instron machine at a speed of 0.5 mm/minute. Prior to the mechanical tests the absence of binding in the device was ruled out. Statistical analysis consisted of the Kruskal-Wallis test and multiple non-parametric analyses at a 1% significance level. RESULTS: When a 0.014-in archwire was employed, all ligation methods exhibited classical friction forces close to zero, except Morelli brackets with new and old elastomeric ligatures, which displayed 64 and 44 centiNewtons, respectively. When a 0.019 x 0.025-in archwire was employed, all ligation methods exhibited values close to zero, except the In-Ovation brackets, which yielded 45 cN, and the Morelli brackets with new and old elastomeric ligatures, which displayed 82 and 49 centiNewtons, respectively. CONCLUSIONS: Damon MX, Easy Clip, Smart Clip, Synergy bracket systems and 8-shaped ligatures proved to be equally effective alternatives for controlling classical friction using 0.014-in nickel-titanium archwires and 0.019 x 0.025-in steel archwires, while the In-Ovation was efficient with 0.014-in archwires but with 0.019 x 0.025-in archwires it exhibited friction that was similar to conventional brackets with used elastomeric ligatures.