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.     

A new metaheuristic for optimization: Optics inspired optimization (OIO)

Due to the law of reflection, a concave reflecting surface/mirror causes the incident light rays to converge and a convex surface/mirror causes the light rays to reflect away so that they all appear to be diverging. These converging and diverging behaviors cause that the curved mirrors show different image types depending on the distance between the object and the mirror. We model such optical phenomena metaphorically into the searching process of numerical optimization by a new algorithm called optics inspired optimization (OIO). OIO treats the surface of the numerical function to be optimized as a reflecting surface in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each individual is assumed to be an artificial object (or light point) that its artificially glittered ray is reflected back by the function surface, given that the surface is convex or concave, and the artificial image is formed (a candidate solution is generated within the search domain) based on the mirror equations adopted from physics of optics. Besides OIO, we introduce different variants of it, called ROIO (Rotation based OIO), and COIO (Convex combination based OIO) algorithms and conduct an extensive computational effort to find out the merit of the new algorithms. Our comparisons on benchmark test functions and a real world engineering design application (i.e., optimization of a centrifuge pump) demonstrate that the new algorithms are efficient and compete better than or similar to most of state of the art optimization algorithms with the advantage of accepting few input parameters.     

Optimal resilient power grid operation during the course of a progressing wildfire

We study a two-stage stochastic and nonlinear optimization model for operating a power grid exposed to a natural disaster. Although this approach can be generalized to any natural hazard of continuous (and not instantaneous) nature, our focus is on wildfires. We assume that an approaching wildfire impacts the power grid by reducing the transmission capacity of its overhead lines. At the time when proactive decisions have to be taken, the severity of the wildfire is not known. This introduces uncertainty. In this paper, we extend previous work by more realistically capturing this uncertainty and by strengthening the mathematical programming formulation through standard reformulation techniques. With these reformulation techniques, the resulting two-stage, convex mixed-integer quadratically constrained programming formulation can be efficiently solved using commercial quadratic programming solvers as demonstrated on a case study on a modified version of the IEEE 123-bus test system with 100 scenarios. We also quantify the uncertainties through a second case study using the following three standard metrics of two-stage stochastic optimization: the expected value of perfect information, the expected result of using the expected value solution and the value of the stochastic solution.     

Computational studies on the radiative and nonradiative processes of luminescent N-heteroleptic platinum(II) complexes

Three N-heteroleptic Pt(II) complexes, [Pt(C^C)(O^O)] [O^O = acetylacetonate, C^C = 1-phenyl-1,2,4-triazol-5-ylidene (1), C^C = 4-phenyl-1,2,4-triazol-5-ylidene (2), C^C = 2-phenylpyrazine (3)] have been investigated with density functional theory (DFT) and time-dependent density functional theory (TDDFT). The radiative decay rate constants of complexes 1–3 have been discussed with the oscillator strength (f_n), the strength of spin–orbit coupling (SOC) interaction between the lowest energy triplet excited state (T₁) and singlet excited states (S_n), and the energy gaps between E(T₁) and E(S_n). To illustrate the nonradiative decay processes, the transition states between triplet metal-centered (³MC) and T₁ states have been optimized and were verified with the calculations of vibrational frequencies and intrinsic reaction coordinate (IRC). In addition, the minimum energy crossing points (MECPs) between ³MC and ground states (S₀) were optimized. At last, the potential energy curves relevant to the nonradiative decay pathways are simulated. The results show that complex 3 has the biggest photoluminescence quantum yield because the complex 3 has the biggest radiative decay rate constant and the smallest nonradiative decay rate constant in complexes 1–3.