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This paper mainly deals with the oscillation of nonlinear delay differential equation which is used to describe advertising capital model, analytically and numerically. Firstly, the condition of oscillation of the analytic solution is presented by the technique of the theory of characteristic. Secondly, the asymptotic behavior of non-oscillatory analytic solution is verified. Thirdly, the θ-methods are applied to the mentioned equation, some conditions under which the numerical solution oscillates are obtained. Moreover, it is proved that every non-oscillatory numerical solution tends to the steady state of the model. Finally, some numerical simulations for verifying the theoretical findings are provided.

We propose a many-objective optimization algorithm based on IGD indicator and region decomposition in this paper. We divide the objective space into multiple sub-regions by a set of direction vectors. Individuals in each sub-region are compared independently. There are some individuals in each sub-region, which can improve the diversity of algorithm. In the selection of operator, we select individuals according to rank first, and then we design different selection methods in different ranks to select individuals with good performance. In the experiment, we compare the proposed algorithm with MaOEA/IGD in 12 test functions with 10 to 20 objectives, and the results show that the proposed algorithm is effective.

This paper proposes an adaptive fireworks algorithm based on simulated annealing to solve global optimization problems. It normalizes the individuals before the explosion operation and then restores them after the explosion operation. The subpopulations are produced simultaneously by the explosion operation and the mutation operation, and then a new way to produce the explosion amplitude by introducing the simulated annealing is used to adjust the explosion amplitude adaptively along with the evolution. Experimental results on eight benchmark functions with different shift values show that the proposed algorithm has higher accuracy and faster convergence rate than the other five compared algorithms.

This paper studies the problem of underdetermined blind source separation with the nonstrictly sparse condition. Different from current approaches in literature, we propose a new and more effective algorithm to estimate the mixing matrices resulted from noise output data sets. After we introduce a clustering prototype of orthogonal complement space and give an extension of the normal vector clustering prototype, a new method combing the fuzzy clustering and eigenvalue decomposition technique to estimate the mixing matrix is presented in order to deal with the nonstrictly sparse situation. A convergent algorithm for estimating the mixing matrices is established, and numerical simulations are given to demonstrate the effectiveness of the proposed approach.

This article is concerned with the stability analysis of the analytic and numerical solutions of a partial differential equation with piecewise constant arguments of mixed type. First, by means of the similar technique in Wiener and Debnath [Int J Math Math Sci 15 (1992), 781–788], the sufficient conditions under which the analytic solutions asymptotically stable are obtained. Then, the θ-methods are used to solve the above-mentioned equation, the sufficient conditions for the asymptotic stability of numerical methods are derived. Finally, some numerical experiments are given to demonstrate the conclusions.Copyright © 2013 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 30: 1-16, 2014

We consider the oscillations of numerical solutions for the nonlinear delay differential equations in the control of erythropoiesis. The exponentialθ-method is constructed and some conditions under which the numerical solutions oscillate are presented. Moreover, it is proven that every nonoscillatory numerical solution tends to the equilibrium point of the continuous system. Numerical examples are given to illustrate the main results.

Within the learning framework of maximum weighted likelihood (MWL) proposed by Cheung, 2004 and 2005, this paper will develop a batch Rival Penalized Expectation-Maximization (RPEM) algorithm for density mixture clustering provided that all observations are available before the learning process. Compared to the adaptive RPEM algorithm in Cheung, 2004 and 2005, this batch RPEM need not assign the learning rate analogous to the Expectation-Maximization (EM) algorithm (Dempster et al., 1977), but still preserves the capability of automatic model selection. Further, the convergence speed of this batch RPEM is faster than the EM and the adaptive RPEM in general. The experiments show the superior performance of the proposed algorithm on the synthetic data and color image segmentation.

In this paper, we study the dynamics of a nonlinear delay differential equation applied in a nonstandard finite difference method. By analyzing the numerical discrete system, we show that a sequence of Neimark–Sacker bifurcations occur at the equilibrium as the delay increases. Moreover, the existence of local Neimark–Sacker bifurcations is considered, and the direction and stability of periodic solutions bifurcating from the Neimark–Sacker bifurcation of the discrete model are determined by the Neimark–Sacker bifurcation theory of discrete system. Finally, some numerical simulations are adopted to illustrate the corresponding theoretical results.

This paper, based on the concern that a large quantity of affected spots, relatively concentrated distribution and a small quantity of emergency materials in the affected area. It addresses an optimized mathematical model and presents a new optimal vehicle routing on emergency relief materials with the goals of the shortest transport time in emergency materials allocation. Firstly the K-means clustering algorithm is adopted to get some of local distribution centersand their distribution scopes, and then particle swarm optimization algorithm is used to design the local optimal allocation routings of emergency relief vehicles inside each scope. Finally, numerical results of the approximately optimal vehicle routings indicate the feasibility and validity of the model and the new algorithm.

This paper propose a method to deal with the complex nonlinear characteristics, which was caused by the uncertainty of the unknown. As the received signal strength is low in Non line-of-sight environment, the proposed algorithm can be used to process and predict the unknown nodes position by maximum likelihood estimation method. Furthermore, experimental results show that the mobile target tracking error can be less than 1m when we use the method mentioned above, thus meeting the requirements of smart space mobile targeting.

This paper proposes a new fast method for identifying the mixing matrix based on a binary state mixture of Gaussian (MoG) source model. First, a necessary discussion for solving the mixing matrix detection is offered under the multiple dominant circumstance. Second, a density detection method is presented to improve the identification performance. Simulations are given to demonstrate the effectiveness of our proposed approach.

A set of matrices is said to have the finiteness property if the maximal rate of growth of long products of matrices taken from the set can be obtained by a periodic product. We study the finite-step realizability of the joint/generalized spectral radius of a pair of n × n square matrices. Let Σ = {A, B} where A,B are n × n matrices and B is a rank-one matrix. Then we have ρ(Σ)= max:t,s ρ(AtBs)1/(s+t). That is to say, Σ have the finiteness property where the maximum is attained at (t, s) with the optimal sequence AtBs.

In this paper, we consider the oscillations of numerical solutions for the nonlinear delay differential equations in a hematopoiesis model. Using two θ-methods, namely the linear θ-method and the one-leg θ-method, several conditions, under which the numerical solutions oscillate, are obtained. Moreover, it is proved that every non-oscillatory numerical solution tends to an equilibrium point of the original system. Some numerical experiments are provided to support the theoretical results. MSC:65L05, 65L20.

This paper focuses on the stability and oscillations of Euler-Maclaurin method for linear differential equations with piecewise constant arguments ${u}^{\prime }\mathbf{\left(}t\mathbf{\right)} \mathbf{=} au\mathbf{\left(}t\mathbf{\right)} \mathbf{+} bu\mathbf{\left(}\mathbf{\left[}t\mathbf{\right]}\mathbf{\right)}$ . The necessary and sufficient conditions under which the numerical stability region contains the analytical stability region are given. Furthermore, the conditions of oscillation for the Euler-Maclaurin method are obtained. We prove that the Euler-Maclaurin method preserves the oscillations of the analytic solution. Moreover, the relationships between stability and oscillations are discussed for analytic solution and numerical solution, respectively. Finally, some numerical experiments for verifying the theoretical analysis are also provided.

The unidirectional logistics distribution vehicle routing problem with no time windows is considered. It contains the vehicle capacity restriction, the longest distance restriction and the full loaded vehicle. The solution must ensure the non-full loaded factor is the least and the total distance is the shortest. A multi-objective optimization mathematical model for the problem is established. And the differential evolution algorithm is proposed for this problem. The optimal solutions to the model are obtained by selecting the appropriate encoding method. The results of simulation show that the differential evolution algorithm is an effective way for solving the vehicle routing problem.

This paper deals with the oscillations of numerical solutions for the nonlinear delay differential equations in physiological control systems. The exponentialθ-method is applied top′(t)=β0ωμp(t−τ)/(ωμ+pμ(t−τ))−γp(t)and it is shown that the exponentialθ-method has the same order of convergence as that of the classicalθ-method. Several conditions under which the numerical solutions oscillate are derived. Moreover, it is proven that every nonoscillatory numerical solution tends to positive equilibrium of the continuous system. Finally, the main results are illustrated with numerical examples.

Numerical oscillation of Runge-Kutta methods for differential equations with piecewise constant arguments is considered in this paper. The conditions of oscillation for the Runge-Kutta methods are obtained. It is proven that the numerical oscillation on the integer nodes are equivalent to the numerical oscillation on the any nodes and oscillation of the analytic solution is preserved by the Runge-Kutta methods. Moreover, the relationship between stability and oscillation is discussed for analytic solution and numerical solution, respectively. At last, several numerical simulations are carried out to support the theoretical analysis of the research.

Based on Bernoulli-Gaussian model and the sparseness of source signals, a new algorithm for estimating the mixing matrix is proposed in this paper. It estimates the mixing matrix by searching the cluster points which are found through the density of points in the region. In order to enhance the precision of the algorithm, the cost function is constructed to search the cluster points. The last simulations show the good performance of the proposed algorithm.

This paper proposes a new kind of constraint handling method for optimization. In the proposed method, a transformation of constraint functions to be another objective function will be discussed in details. With this technique we can transform the constraint problem to be unconstraint multiobjective optimization and use the multi-objective optimization methods to find feasible solutions. The performance of the algorithm is tested on 13 benchmark functions in the literature. The results show that we can find very good solutions by this approach.

In this paper, the difference of satisfactions for fuzzy yield and fuzzy risk from investors is viewed as a fuzzy number with parabolic membership function, and a fuzzy decision securities investment combination model bases on parabolic satisfaction degree is constructed with fuzzy set and fuzzy decision theories. The experimental results on real-word data show that our new approach is very efficient and effective for the investment decision.

Optimization method with triangular fuzzy numbers is introduced to describe the expected yield rate and risk loss of securities investment, and a combinational fuzzy optimization model of inclinations with exchange fee to avoid risks is presented in this paper. The experimental results on the data investigated from real-world securities markets show that our new method exploits a new strategy for the investment decision.

For the problem of Underdetermined Blind Source Separation (UBSS) under nonstrictly sparse condition, we propose a new algorithm to estimate mixing matrix. Firstly, a clustering prototype of orthogonal complement space is introduced; Secondly, a fuzzy EVD clustering method which combines fuzzy clustering and Eigenvalue Decomposition (EVD) is presented. Based on these two methods, the algorithm proposed in this paper is robust against noise without losing convergence speed.

In this paper, we propose a decomposition-based evolutionary algorithm with boundary search and archive for constrained multi-objective optimization problems (CMOPs), named CM2M. It decomposes a CMOP into a number of optimization subproblems and optimizes them simultaneously. Moreover, a novel constraint handling scheme based on the boundary search and archive is proposed. Each subproblem has one archive, including a subpopulation and a temporary register. Those individuals with better objective values and lower constraint violations are recorded in the subpopulation, while the temporary register consists of those individuals ever found before. To improve the efficiency of the algorithm, the boundary search method is designed. This method makes the feasible individuals with a higher probability to perform genetic operator with the infeasible individuals. Especially, when the constraints are active at the Pareto solutions, it can play its leading role. Compared with two algorithms, i.e. CMOEA/D-DE-CDP and Gary’s algorithm, on 18 CMOPs, the results show the effectiveness of the proposed constraint handling scheme.