Global exponential stability of high order recurrent neural network with time-varying delays

In this paper, global exponential stability of high order recurrent neural network with time-varying delay and bounded activation functions is investigated. Some improved conditions are obtained involving external input, connection weights, and time delays of recurrent neural network. Moreover, the location of the equilibrium point can be estimated. In addition, two examples are demonstrated to illustrate the effectiveness of the proposed criteria in comparison with some existing results.     

Surmounting the Multiple-Minima Problem in Protein Folding

Protein folding is a very difficult global optimization problem. Furthermore it is coupled with the difficult task of designing a reliable force field with which one has to search for the global minimum. A summary of a series of optimization methods developed and applied to various problems involving polypeptide chains is described in this paper. With recent developments, a computational treatment of the folding of globular proteins of up to 140 residues is shown to be tractable.     

A hybrid neuro-fuzzy analytical approach to mode choice of global logistics management

This paper presents a hybrid neuro-fuzzy methodology to identify appropriate global logistics (GL) operational modes used for global supply chain management. The proposed methodological framework includes three main developmental phases: (1) establishment of a GL strategic hierarchy, (2) formulation of GL-mode identification rules, and (3) development of a GL-mode choice model. By integrating advanced multi-criteria decision-making (MCDM) techniques including fuzzy analytical hierarchy process (Fuzzy-AHP), Fuzzy-MCDM, and the technique for order preference by similarity to an ideal solution (TOPSIS), six types of global logistics and operational modes coupled with corresponding fuzzy-based multi-criteria decision-making rules are specified in the second phase. Using the specified fuzzy decision-making rules as the input database, an adaptive neuro-fuzzy inference system (ANFIS) is then developed in the third phase to identify proper GL modes for the implementation of global supply chain management. A numerical study with a questionnaire survey database aimed at the information technology (IT) industries of Taiwan is conducted to illustrate the applicability of the proposed method.     

A note on “A Continuous Approach to Nonlinear Integer Programming”

Ge and Huang (1989) proposed an approach to transform nonlinear integer programming problems into nonlinear global optimization problems, which are then solved by the filled function transformation method. The approach has recently attracted much attention. This note indicates that the formulae to determine a penalty parameter in two fundamental theorems are incorrect, and presents the corrected formulae and revised theorems.     

Banach 空间中一阶脉冲积分-微分方程初值问题整体解的存在性

通过逐段应用推广的Darbo不动点定理,在较弱的条件下,给出了实Banach空间中一阶脉冲积分-微分方程初值问题整体解的存在性,改进了一些已有的结果.     

The development of a multi-objective Tabu Search algorithm for continuous optimisation problems

While there have been many adaptations of some of the more popular meta-heuristics for continuous multi-objective optimisation problems, Tabu Search has received relatively little attention, despite its suitability and effectiveness on a number of real-world design optimisation problems. In this paper we present an adaptation of a single-objective Tabu Search algorithm for multiple objectives. Further, inspired by path relinking strategies common in discrete optimisation problems, we enhance our algorithm to allow it to handle problems with large numbers of design variables. This is achieved by a novel parameter selection strategy that, unlike a full parametric analysis, avoids the use of objective function evaluations, thus keeping the overall computational cost of the procedure to a minimum. We assess the performance of our two Tabu Search variants on a range of standard test functions and compare it to a leading multi-objective Genetic Algorithm, NSGA-II. The path relinking-inspired parameter selection scheme gives a clear performance improvement over the basic multi-objective Tabu Search adaptation and both variants perform comparably with the NSGA-II.     

一类时滞反应扩散方程的稳态解的全局吸引性

本文研究了一类带扩散项造血生物模型当非线性项不具有单调性时,Dirichlet边值条件下稳态解的全局吸引性.     

A simplicial branch-and-bound algorithm conscious of special structures in concave minimization problems

In this paper, we develop a simplicial branch-and-bound algorithm for generating globally optimal solutions to concave minimization problems with low rank nonconvex structures. We propose to remove all additional constraints imposed on the usual linear programming relaxed problem. Therefore, in each bounding operation, we solve a linear programming problem whose constraints are exactly the same as the target problem. Although the lower bound worsens as a natural consequence, we offset this weakness by using an inexpensive bound tightening procedure based on Lagrangian relaxation. After giving a proof of the convergence, we report a numerical comparison with existing algorithms. T. Kuno was partially supported by the Grand-in-Aid for Scientific Research (C) 17560050 from the Japan Society for the Promotion of Sciences.     

Towards “Ideal Multistart”. A stochastic approach for locating the minima of a continuous function inside a bounded domain

A stochastic global optimization method based on Multistart is presented. In this, the local search is conditionally applied with a probability that takes in account the topology of the objective function at the detail offered by the current status of exploration. As a result, the number of unnecessary local searches is drastically limited, yielding an efficient method. Results of its application on a set of common test functions are reported, along with a performance comparison against other established methods of similar nature.     

A smoothing effect and polynomial growth of the Sobolev norms for the KP-II equation

We prove that the eventual growth in time of the Sobolev norms of the solutions of the KP-II equation is at most polynomial.