Global optimality conditions for quadratic 0-1 programming with inequality constraints

Quadratic 0-1 problems with linear inequality constraints are briefly considered in this paper.Global optimality conditions for these problems,including a necessary condition and some sufficient conditions,are presented.The necessary condition is expressed without dual variables.The relations between the global optimal solutions of nonconvex quadratic 0-1 problems and the associated relaxed convex problems are also studied.

Improved extracellular endo-1,4-β-mannosidase activity of recombinant Pichia pastoris by optimizing signal peptide

In order to improve the extracellular endo-1,4-β-mannosidase(MAN) activity of recombinant Pichia pastoris, optimization of signal peptides was investigated. At first, five potential signal peptides(W1, MF4 I, INU1 A, αpre, HFBI) were chosen to be analyzed by Signal P 4.0, among which W1 was designed. Then, the widely used signal peptide α-factor in expression vector p GAPZαA was replaced by those five signal peptides to reconstruct five new expression vectors. MAN activity was assayed after expression vectors were transformed into Pichia pastoris. The data show that the relative efficiencies of W1, MF4 I, INU1 A, αpre, and HFBI signal peptides are 23.5%, 203.5%, 0, 79.7%, and 120.3% compared with α-factor, respectively. The further gene copy number determination by the quantitative real-time PCR reveals that the MAN activities mediated by α-factor from 1 to 6 gene copy number levels are 12.95, 43.33, 126.63, 173.53, 103.23 and 88.63 U/m L, while those mediated by MF4 I are 79.22, 133.89, 260.14, 347.5, 206.15 and 181.89 U/m L, respectively. The maximum MAN activity reached 347.5 U/m L with 4 gene copies mediated by MF4 I. These results indicate that replacing the signal peptide α-factor with MF4 I and increasing MAN gene copies to a proper number can greatly improve the secretory expression of MAN.

Topology optimization of 3D structures with design-dependent loads

Topology optimization of continuum structures with design-dependent loads has long been a challenge. In this paper, the topology optimization of 3D structures subjected to design-dependent loads is investigated. A boundary search scheme is proposed for 3D problems, by means of which the load surface can be identified effectively and efficiently, and the difficulties arising in other approaches can be overcome. The load surfaces are made up of the boundaries of finite elements and the loads can be directly applied to corresponding element nodes, which leads to great convenience in the application of this method. Finally, the effectiveness and efficiency of the proposed method is validated by several numerical examples.

Al_2O_3-2SiO_2 Nanoparticles with Defined Al-Si Ratio:Processing Optimization and Conversion

Attempts had been made to synthesize Al2O3-2SiO2 nanopowders by sol-gel method with tetraethoxysilane（TEOS） and aluminum nitrate（ANN） as the starting materials.DTS,TEM,SEM and BET were employed to study the effects of process parameters on the size,specific surface area and structure（morphology） of powders.The alkali-activation reactivity of the powders was tested for manufacturing geopolymers and their hydrothermal reactions were performed for fabricating zeolites.The results show that the optimum process parameters and drying method for preparing Al2O3-2SiO2 nanopowders are as follows：the molar ratio of water and ethanol to TEOS are 0：1 and 12：1 respectively at synthetic temperature of 50 ℃ and the drying method is azeotropic distillation with microwave drying.The average particle diameters of the powders were about 70 nm and the largest BET specific surface area was up to 669 m^2·g^-1.The compressive strength of the geopolymer and the calcium exchange capacity（by CaCO3） of NaA zeolite prepared with the powders reached to 29 MPa and 366 m^2·g^-1 respectively.

Fundamental Properties and Optimal Gains of a Steady-State Velocity Measured <i>α</i>-<i>β</i>Tracking Filter

This paper clarifies the steady-state properties and performance of an α-β filter for moving target tracking using both position and velocity measurements. We call this filter velocity measured α-β (VM-α-β) filter. We first derive the stability condition and steady-state predicted errors as fundamental properties of the VM-α-β filter. The optimal gains for representative motion models are then derived from the Kalman filter equations. Theoretical and numerical analyses verify that VM-α-β filters with these optimal gains realize more accurate tracking than conventional α-β filters when the filter gains are relatively large. Our study reveals the conditions under which the predicted errors of the VM-α-β filters are less than those of conventional α-β filters. Moreover, numerical simulations clarify that the variance of the tracking error of the VM-α-β filters is approximately 3/4 of that of the conventional α-β filters in realistic situations, even when the accuracy of the position/velocity measurements is the same.

MODS： A Novel Metaheuristic of Deterministic Swapping for the Multi-Objective Optimization of Combinatorials Problems

This paper states a new metaheuristic based on Deterministic Finite Automata （DFA） for the multi - objective optimization of combinatorial problems. First, a new DFA named Multi - Objective Deterministic Finite Automata （MDFA） is defined. MDFA allows the representation of the feasible solutions space of combinatorial problems. Second, it is defined and implemented a metaheuritic based on MDFA theory. It is named Metaheuristic of Deterministic Swapping （MODS）. MODS is a local search strategy that works using a MDFA. Due to this, MODS never take into account unfeasible solutions. Hence, it is not necessary to verify the problem constraints for a new solution found. Lastly, MODS is tested using well know instances of the Bi-Objective Traveling Salesman Problem （TSP） from TSPLIB. Its results were compared with eight Ant Colony inspired algorithms and two Genetic algorithms taken from the specialized literature. The comparison was made using metrics such as Spacing, Generational Distance, Inverse Generational Distance and No-Dominated Generation Vectors. In every case, the MODS results on the metrics were always better and in some of those cases, the superiority was 100%.

α-氧代膦酸酯类衍生物的CoMFA研究

In this paper,CoMFA studies were performed on a set of α-(substituted phenoxy acetoxy)alkyl phosphonates.On the basis of the 60 molecules and with the help of ’optimizing QSAR’,Nut only not only built model,Which a good CoMFA model,which with the conventional r^2 and crossvalidated coefficient(q^2) up to 0.94 and 0.82,but also 5120 new structures and their predicted activities were obtained.This work provided a potential direction for the further synthesis.

Improved Differential Evolution with Shrinking Space Technique for Constrained Optimization

Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique and adaptive trade-off model, named ATMDE, is proposed to solve constrained optimization problems. The proposed ATMDE algorithm employs an improved differential evolution as the search optimizer to generate new offspring individuals into evolutionary population. For the con- straints, the adaptive trade-off model as one of the most important constraint-handling techniques is employed to select better individuals to retain into the next population, which could effectively handle multiple constraints. Then the shrinking space technique is designed to shrink the search region according to feedback information in order to improve computational efficiency without losing accuracy. The improved DE algorithm introduces three different mutant strategies to generate different offspring into evo- lutionary population. Moreover, a new mutant strategy called ＂DE/rand/best/l＂ is constructed to generate new individuals according to the feasibility proportion ofcurrent population. Finally, the effectiveness of the pro- posed method is verified by a suite of benchmark functions and practical engineering problems. This research presents a constrained evolutionary algorithm with high efficiency and accuracy for constrained optimization problems.

A system-wide approach to minimize the operational cost of bench production in open-cast mining operations

The production cycle of open-cast coal mines generally in eludes drilling, blasting, loading, hauling and coal preparation activities. Individual optimization of these activities does not mean that the whole system is optimized. This paper proposes a cost model considering all activities in mining cycle and system-wide approach to minimize the total mining cost of bench production. Since the fragmentation size and blast-hole diameter are linked to all activities of mining system, they are considered as decision variables in the problem form ul at io n. The operatio n costs are then minimized by using the evolutionary algorithm. Moreover, the impact of the change in the explosive price, and the hourly unit cost of equipment on total mining cost is quantified by sensitivity analysis. A case study is implemented to demonstrate the developed model.

Optimization of the carrier tracking loop for GPS high dynamic receivers

A carrier tracking loop which can adjust the loop parameters adaptively is proposed for high dynamic application. Three modules, called the α-β-γT filter model, adaptive loop structure mod- el and adaptive loop bandwidth model respectively, are added in the presented tracking loop com- pared with the traditional carrier tracking loop based on the second-order frequency lock loop （FLL） assisting third-order phase lock loop （PLL） loop filter. And the optimization methods for the track- ing bandwidth and the carrier loop order are analyzed. The real-time estimation methods of the dy- namic parameters, the velocity, acceleration and jerk along the line of sight （LOS） between the sat- ellite and the receiver＇ s antenna, and the measurement parameters are discussed based on the pres- ented α-β-γ filter algorithm. A method is introduced to improve the filter＇ s dynamic response to meet high dynamic application by self-adjusted α-β-γ filter coefficient used in the tracking loop. The performance of three cases with different carrier tracking loop is compared by simulation.

Optimization Design for Fixed Table of Gantry Machining Center Based on Sensitivity and Topology Analyses

In order to decrease the deformation and stress and increase the natural frequency of the fixed table,a method of optimization driven by the sensitivity and topology analyses is proposed.The finite element model of the fixed table is constructed and analyzed by using ANSYS software.Based on the results of static analysis and modal analysis,the maximum deformation,the maximum stress,and natural frequencies are obtained.Then,the sensitivity analysis and topology optimization are carried out to find out the parameters to be optimized.The fixed table is reconstructed according to optimal design scheme.In the comparison of the results between original model and the optimized one,the maximum deformation and stress are decreased by 71.73%and 60.27%respectively.At the same time,the natural frequencies from the first mode to the sixth mode are increased by 30.28%,29.57%,29.51%,31.52%,22.19%,and 21.80%,respectively.The method can provide technology guide for the design and optimization of machining structure.

Chaotic Neural Network Technique for "0-1" Programming Problems

0-1 programming is a special case of the integer programming, which is commonly encountered in many optimization problems. Neural network and its general energy function are presented for 0-1 optimization problem. Then, the 0-1 optimization problems are solved by a neural network model with transient chaotic dynamics (TCNN). Numerical simulations of two typical 0-1 optimization problems show that TCNN can overcome HNN's main drawbacks that it suffers from the local minimum and can search for the global optimal solutions in to solveing 0-1 optimization problems.

Optimization of Culture Components for Laccase Activity from Pleurotus Ostreatus P40 Using Response Surface Methodology

High enzymatic activity is required for laccase applications.Central composite design （CCD）-based response surface methodology （RSM） can effectively increase the enzymatic activity of Pleurotus ostreatus P40 in liquid substrate fermentation.Initial screening of the nutritional components was performed using a Plackett-Burman design.The variables,namely,bran,bagasse,Tween 80,and yeast extract,were found to have statistically significant effects on laccase activity.These variables were further optimized using CCD-based RSM.Optimal concentrations for the maximum laccase activity were 8.144 2 g/L bran,50 g/L bagasse,0.424 1 mL/L Tween 80,and 2.832 5 g/L yeast extract.Under optimized conditions,the maximum measured laccase activity reached 96 480 U/L,which was close to the predicted value （104 830 U/L） by RSM.Therefore,RSM can be used to optimize culture components for laccase activity from Pieurotus ostreatus P40.

An Algorithm of 0-1 Knapsack Problem Based on Economic Model

In order to optimize the knapsack problem further, this paper proposes an innovative model based on dynamic expectation efficiency, and establishes a new optimization algorithm of 0-1 knapsack problem after analysis and research. Through analyzing the study of 30 groups of 0-1 knapsack problem from discrete coefficient of the data, we can find that dynamic expectation model can solve the following two types of knapsack problem. Compared to artificial glowworm swam algorithm, the convergence speed of this algorithm is ten times as fast as that of artificial glowworm swam algorithm, and the storage space of this algorithm is one quarter that of artificial glowworm swam algorithm. To sum up, it can be widely used in practical problems.

Robust Optimization of Performance Scheduling Problem under Accepting Strategy

In this paper, the problem of program performance scheduling with accepting strategy is studied. Considering the uncertainty of actual situation, the duration of a program is expressed as a bounded interval. Firstly, we decide which programs are accepted. Secondly, the risk preference coefficient of the decision maker is introduced. Thirdly, the min-max robust optimization model of the uncertain program show scheduling is built to minimize the performance cost and determine the sequence of these programs. Based on the above model, an effective algorithm for the original problem is proposed. The computational experiment shows that the performance’s cost (revenue) will increase (decrease) with decision maker’s risk aversion.

Nondifferentiable Multiobjective Programming under Generalized d_I-G-Type I Invexity

To relax convexity assumptions imposed on the functions in theorems on sufficient conditions and duality,new concepts of generalized dI-G-type Ⅰ invexity were introduced for nondifferentiable multiobjective programming problems.Based upon these generalized invexity,G-Fritz-John （G-F-J） and G-Karnsh-Kuhn-Tucker （G-K-K-T） types sufficient optimality conditions were established for a feasible solution to be an efficient solution.Moreover,weak and strict duality results were derived for a G-Mond-Weir type dual under various types of generalized dI-G-type Ⅰ invexity assumptions.

A New Searching Strategy for the Lost Plane Based on RBF Neural Network Model and Global Optimization Model

In this paper, we construct two models for the searching task for a lost plane. Model 1 determines the searching area. We predict the trajectory of floats generated after the disintegration of the plane by using RBF neural network model, and then determine the searching area according to the trajectory. With the pass of time, the searching area will also be constantly moving along the trajectory. Model 2 develops a maritime search plan to achieve the purpose of completing the search in the shortest time. We optimize the searching time and transform the problem into the 0-1 knapsack problem. Solving this problem by improved genetic algorithm, we can get the shortest searching time and the best choice for the search power.

Probing the effects of lithium doping on structures, properties, and stabilities of magnesium cluster anions

Bimetallic clusters have aroused tremendous interest because the property changes like structure,size,and composition have occurred.Herein,a structural search of the global minimum for anionic LiMg_(n)^(-)(n=2-11) clusters is performed using an efficient crystal structure analysis by particle swarm optimization(CALYPSO) structural searching program with subsequent density functional theory(DFT) calculations.A great variety of low energetic isomers are converged,and the most stable ones are confirmed by comparing their total energy of each size.It is found that the LiMg_(n)^(-)clusters are structurally consistent with corresponding Mg clusters anions except for LiMg_(5)^(-)and LiMg_(7)^(-).In all the doped clusters,the Li atom prefers to occupy the convex position.Simulated photoelectron spectra(PES),Infrared(IR),and Raman spectra of LiMg_(n)^(-)could be used as an essential evidence for identifying cluster structures experimentally in the future.Stability study reveals that a tower-like structure of LiMg_(9)^(-)has prominent stability and can be identified as a magic number cluster.The reason might be that there are both closed-shell 1S^(2)1P^(6)1D^(10)2S^(2) electronic configurations and stronger Li-Mg bonds caused by sp hybridization in the LiMg_(9)^(-)cluster.

一种新型的非线性积分器

提出一种新型的非线性积分器，给出它的数学模型，并用谐波线性化原理讨论它的频率特性，其幅频特性起积分作用，而相位滞后仅２７６°，高次谐波分量小，抗干扰能力强．应用这种积分器设计了一个双目标优化的二次优化系统．仿真结果表明，系统的控制性能好，具有广泛的应用前景．

二次优化雷达伺服系统

本文提出一类新型非线性控制器和二次优化控制系统大相角裕量设计法．应用这些结果对线性优化系统进行优化．可以获得性能指标比线性优化系统好得多的二次优化系统．文中给出用大相角裕量二次优化设计法来设计大型雷达伺服系统的实例，并作计算机仿真校验其性能指标．结果表明，二次优化系统的性能指标确比线性优化系统好．设计方法简便，通用、适用于工程设计．