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.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

An optimization model for evaluating the economic impact of availability and maintenance notions during the synthesis and design of a power plant

In this paper, we introduce an optimization strategy in order to comprehensively quantify the impact of availability and maintenance notions during the early stages of synthesis and design of a new natural gas combined cycle power plant. A detailed state-space approach is thoroughly discussed, where influence of maintenance funds on each component's repair rate is directly assessed.In this context, analysis of the reliability characteristics of the system is centered at two designer-adopted parameters, which largely influence the obtained results: the number of components which may fail independently at the same time, and the number of simultaneous failure/repair events.Then, optimal solutions are evaluated as the availability-related parameters and the amount of resources assigned for maintenance actions are varied across a wide range of feasible values, which enable obtaining more accurate and detailed estimations of the expected economic performance for the project when compared with traditional economic evaluation approaches.     

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.     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

Seawater-softening process through formation of calcite ooids

Conventional water-softening processes usually involve the exchange of Na⁺ ions for Ca²⁺ and Mg²⁺ using commercial or synthesized ion exchangers. The differences in chemical compositions of the ooids can be attributed to the formation in different environments. In this paper, ooid grains form inside assembled semi-pilot softening unit through a continuous chemical process involving reaction between bicarbonate ions and added lime using natural seawater. Our sample of Mediterranean seawater has low Mg²⁺/Ca²⁺ ratio (1.98%) within the range chemically favorable for precipitation of low-Mg calcite ooids. Precipitation of calcite occurs around pure quartz sand grains which act as nucleation points (the bed required for sand vessel is 1.65 l). The shape of the sand grains controls the overall external morphology of the resulting ooids; they vary in size from 0.5 to 3.0 mm and have a high degree of polish due to surface abrasion caused by continuous agitation inside the softening system. Calcite ooid grains (1.53 kg) formed within the seawater-softening unit every 18 days have many of the ooid features formed in marine environments. Ooids grow to a significant size, at a rate of about 0.17 mm of one layer thickness per day inside the softening unit. The average weight percent of calcite precipitate is 35.48% after 18 days, at 10 °C, 60 l/min and pH 9.0. The pellets comprise mainly CaCO₃ and SiO₂ and some metal ions which may substitute for calcium ions in calcite are present only in trace amounts of the total composition.     

浅谈氯碱氢的一种深度脱水工艺

概述了氢的主要工业生产方法和实际应用,详细介绍了氯碱氢三级脱水工艺过程,并运用在线分析手段,准确显示了干燥过程中的氯碱氢水分含量变化规律。     

Kariya (Hildegardia barteri) seed oil extraction: comparative evaluation of solvents,modeling, and optimization techniques

In this work, the effects of solid/solvent ratio (0.10–0.25?g/ml), extraction time (3–8?h), and solvent type (n-hexane, ethyl acetate, and acetone) together with their shared interactions on Kariya seed oil (KSO) yield were investigated. The oil extraction process was modeled via response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) while the optimization of the three input variables essential to the oil extraction process was carried out by genetic algorithm (GA) and RSM methods. The low mean relative percent deviation (MRPD) of 0.94–4.69% and high coefficient of determination (R²) > 0.98 for the models developed demonstrate that they describe the solvent extraction process with high accuracy in this order: ANFIS, ANN, and RSM. The best operating condition (solid/solvent ratio of 0.1?g/ml, extraction time of 8?h, and acetone as solvent of extraction) that gave the highest KSO yield (32.52?wt.%) was obtained using GA-ANFIS and GA-ANN. Solvent extraction efficiency evaluation showed that ethyl acetate, n-hexane, and acetone gave maximum experimental oil yields of 19.20?±?0.28, 25.11?±?0.01, and 32.33?±?0.04?wt.%, respectively. Properties of the KSO varied based on the type of solvent used. The results of this work showed that KSO could function as raw material in both food and chemical industries.     

Hydroxyapatite/tricalcium silicate composites cement derived from novel two-step sol-gel process with good biocompatibility and applications as bone cement and potential coating materials

Tricalcium silicate (C₃S) and hydroxyapatite (HAp) composites were fabricated through the sol-gel process. The aim of this research is to improve the biocompatibility of C₃S through HAp addition and study the potential of using this as coating materials. The composites (HAp/C₃S) were characterised by Fourier transform infrared spectrometry, thermal gravity-differential thermal analysis and X-ray diffraction. The working and setting times of cement pastes were tested using Gillmore needle. Mechanical properties were examined by nanoindentation and material testing system. In vitro biocompatibility of the materials were studied by cell attachment and viability of L929 and MG-63 cells. HAp/C₃S as a coating material on gelatin film were measured with the surface roughness and imaged by scanning electron microscope. With the addition of HAp, no undesirable free CaO was detected with the synthesis by the sol-gel preparation. The pH values of HAp added groups were between 7.54 and 8.76, which were much lower than pure C₃S group (pH?=?11.75). For in vitro studies, the presence of HAp could effectively enhance the cell attachment and viability of both L929 and MG-63 cells grown in the extract or directly on the composites. However, the mechanical properties of the composites were impaired as compared to pure C₃S. Lastly, HAp/C₃S cement could be evenly coated on gelatin film. HAp is successfully demonstrated to improve C₃S biocompatibility with this new composites HAp/C₃S. C-75 (75% C₃S and 25% HAp), in particular, has good biocompatibility, relatively high compressive strength and can be uniformly coated onto gelatin film. Thus, C-75 is a promising material for further investigation as a coating on other biopolymers.