Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization

For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence.     

On recommendation problems beyond points of interest

Recommendation systems aim to recommend items or packages of items that are likely to be of interest to users. Previous work on recommendation systems has mostly focused on recommending points of interest (POI), to identify and suggest top-k items or packages that meet selection criteria and satisfy compatibility constraints on items in a package, where the (packages of) items are ranked by their usefulness to the users. As opposed to prior work, this paper investigates two issues beyond POI recommendation that are also important to recommendation systems. When there exist no sufficiently many POI that can be recommended, we propose (1) query relaxation recommendation to help users revise their selection criteria, or (2) adjustment recommendation to guide recommendation systems to modify their item collections, such that the users׳ requirements can be satisfied.We study two related problems, to decide (1) whether the query expressing the selection criteria can be relaxed to a limited extent, and (2) whether we can update a bounded number of items, such that the users can get desired recommendations. We establish the upper and lower bounds of these problems, all matching, for both combined and data complexity, when selection criteria and compatibility constraints are expressed in a variety of query languages, for both item recommendation and package recommendation. To understand where the complexity comes from, we also study the impact of variable sizes of packages, compatibility constraints and selection criteria on the analyses of these problems. Our results indicate that in most cases the complexity bounds of query relaxation and adjustment recommendation are comparable to their counterparts of the basic recommendation problem for testing whether a given set of (resp. packages of) items makes top-k items (resp. packages). In other words, extending recommendation systems with the query relaxation and adjustment recommendation functionalities typically does not incur extra overhead.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

Thermal imaging of time-varying longitudinal defects in the internal coating of a tube

We deal with the mathematical model of the incremental degradation of the internal coating (e.g. a polymeric material) of a metallic pipe in which a fluid flows relatively fast. The fluid drags solid impurities so that longitudinal scratches, inaccessible to any direct inspection procedure, are produced on the coating. Time evolution of this kind of defects can be reconstructed from the knowledge of a sequence of temperature maps of the external surface. The time-varying orthogonal section of this damaged interface is determined as a function of time and polar angle through the identification of a suitable effective heat transfer coefficient by means of Thin Plate Approximation.     

Ions motion algorithm for solving optimization problems

This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.     

Recension des écrits sur l'impact des contacts sexuels précoces sur les hommes.

A review of the literature on the impact of sexual contacts between adults and boys reveals the existence of two principal outcomes: 1) some participants develop various disorders once in adulthood, such as behavioural problems, sexual disorders, or personality problems; 2) some participants do not present with any major disorders in the long run. These different outcomes may be associated with several moderating variables related to the sexual contacts, such as the level of coercion at the time of these contacts, the bond between the child and the adult, or the context of the sexual relation. However, the conclusions relating to the relations between early sexual contacts with adults and subsequent problems of adaptation in adulthood are difficult to determine. This is because of various methodological problems associated with relevant studies (i.e., definition of these contacts, nature of the sample, method evaluation, statistical analyses). In this article, we propose certain avenues of research that may help clarify this problem. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Preschool Competency in Context: An Investigation of the Unique Contribution of Child Competencies to Early Academic Success.

The present concurrent study combined developmental and ecological considerations to examine the unique contribution of multiple preschool competencies to an indicator of early academic success. Participants included 195 Head Start children from 32 classrooms representative of a large, urban Head Start program. Dimensional (variable-centered) analyses revealed 3 distinct classroom competency dimensions (i.e., General Classroom Competencies, Specific Approaches to Learning, and Interpersonal Classroom Behavioral Problems). The first 2 of these dimensions were found to be uniquely associated with early academic success. Findings from typological (person-centered) analyses supported the dimensional findings. Typological analyses revealed 7 profiles of classroom competency distinguished by high scores on the dimensions of General Competencies and Approaches to Learning, and these profiles were found to relate differentially to the indicator of early academic success. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

规整填料和新型塔板设计参数选取的质疑及分析

笔者指出了目前规整填料和新型塔板设计计算中若干尚未完全解决的、有争议或值得进一步完善的设计参数。如:规整填料的每米理论板数、最小液体喷淋密度、最小气体空塔动能因子、新型塔板开孔率等,并提出了具体的设计方案供与同行切磋。     

Profiling Voids Embedded in a Slab by a Non-Linear Model

In this paper, by applying a non linear model for the electromagnetic inverse scattering, a technique for the dielectric profiling of a planarly layered medium is investigated and applied to void localization and diagnostics inside a homogeneous lossless slab (one-dimensional geometry). Data are collected under plane wave multifrequency normal incidence. Suitable finite dimensional representations for the unknown functions are introduced and their influence on the model is discussed. The resulting functional equation is solved by the method of weighted residuals and the solution algorithm amounts to minimizing a non quadratic function, where particular attention is devoted to reduce the occurrence of local minima. Finally, the inversion algorithm is validated by applications to both simulated and experimental data.