Output-feedback synchronization of chaotic systems based on sum-of-squares approach

This paper investigates the synchronization of chaotic systems using an output feedback polynomial controller. As only output system states are considered, it makes the controller design and system analysis more challenging compared to the full-state feedback control schemes. To study the system stability and synthesize the output feedback polynomial controller, Lyapunov stability theory is employed. Sufficient stability conditions are derived in terms of sum of squares (SOS) conditions to guarantee the system stability and aid the controller synthesis. A genetic algorithm-based SOS technique is proposed to find the solution to the SOS conditions and the parameter values of the output feedback polynomial controller. A simulation example is employed to illustrate the effectiveness of the proposed approach.     

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.     

A savings based method for real-life vehicle routing problems

This paper describes a Savings Based algorithm for the Extended Vehicle Routing Problem. This algorithm is compared with a sequential insertion algorithm on real-life data. Besides the traditional quality measures such as total distance travelled and total workload, we compare the routing plans of both algorithms according to non-standard quality measures that help to evaluate the ‘visual attractiveness’ of the plan. Computational results show that, in general, the savings based algorithm not only performs better with respect to these non-standard quality measures, but also with respect to the traditional measures.     

A general approach for optimizing regular criteria in the job-shop scheduling problem

Even though a very large number of solution methods has been developed for the job-shop scheduling problem, a majority has been designed for the makespan criterion. In this paper, we propose a general approach for optimizing any regular criterion in the job-shop scheduling problem. The approach is a local search method that uses a disjunctive graph model and neighborhoods generated by swapping critical arcs. The connectivity property of the neighborhood structure is proved and a novel efficient method for evaluating moves is presented. Besides its generality, another prominent advantage of the proposed approach is its simple implementation that only requires to tune the range of one parameter. Extensive computational experiments carried out on various criteria (makespan, total weighted flow time, total weighted tardiness, weighted sum of tardy jobs, maximum tardiness) show the efficiency of the proposed approach. Best results were obtained for some problem instances taken from the literature.     

An irregular grid approach for pricing high-dimensional American options

We propose and test a new method for pricing American options in a high-dimensional setting. The method is centered around the approximation of the associated complementarity problem on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE representation of the underlying process and computing the root of the transition probability matrix of an approximating Markov chain. Experimental results in five-dimensions are presented for four different payoff functions.     

免疫逃避型粒子群优化算法

针对基本粒子群优化算法容易陷入局部极值的缺陷,提出了一种免疫逃避型粒子群优化算法.其基本思想是将初始粒子群划分为寄生与宿主两个种群以模拟生物寄生行为,对寄生种群的粒子采用精英学习策略,对宿主群的粒子采用探索策略,再引入免疫系统的高频变异对寄生群采用相应的免疫逃避机制,以增强群体逃离局部极值、提高算法的全局寻优能力.采用标准测试函数的实验结果表明,该算法在收敛速度和求解精度方面均有显著改进.     

A multicriteria approach for optimizing bus schedules and school starting times

In many rural counties pupils on their way to school are a large, if not the largest group of customers for public mass transit. Hence an effective optimization of public mass transit in these regions must include the traffic caused by pupils. Besides a change in the schedules of the buses and the starting times of the trips, the school starting time may become an integral part of the planning process. We discuss the legal framework for this optimization problem in German states and counties and present a multi-objective mixed-integer linear programming formulation for the simultaneous specification of school and trip starting times. For its solution, we develop a two-stage decomposition heuristic and apply it to practical data sets from three different rural German counties.     

An algorithmic approach for maintenance management based on advanced state space systems and harmonic regressions

Point mechanisms are special track elements which failures results in delays and increased operating costs. In some cases such failures cause fatalities. A new robust algorithm for fault detection of point mechanisms is developed. It detects faults by comparing what can be considered the ‘normal’ or ‘expected’ shape of some signal with respect to the actual shape observed as new data become available. The expected shape is computed as a forecast of a combination of models. The proposed system deals with complicated features of the data in the case study, the main ones being the irregular sampling interval of the data and the time varying nature of the periodic behaviour. The system models are set up in a continuous-time framework and the system has been tested on a large dataset taken from a point mechanism operating on a commercial line.     

A least-squares approach based on a discrete minus one inner product for first order systems

The purpose of this paper is to develop and analyze a least-squares approximation to a first order system. The first order system represents a reformulation of a second order elliptic boundary value problem which may be indefinite and/or nonsymmetric. The approach taken here is novel in that the least-squares functional employed involves a discrete inner product which is related to the inner product in (the Sobolev space of order minus one on ). The use of this inner product results in a method of approximation which is optimal with respect to the required regularity as well as the order of approximation even when applied to problems with low regularity solutions. In addition, the discrete system of equations which needs to be solved in order to compute the resulting approximation is easily preconditioned, thus providing an efficient method for solving the algebraic equations. The preconditioner for this discrete system only requires the construction of preconditioners for standard second order problems, a task which is well understood.

     

A Lagrangean relaxation based approach for the capacity allocation problem in flexible manufacturing systems

This study considers the operation assignment and capacity allocation problem in flexible manufacturing systems. A set of operations is selected to be processed and assigned to the machines together with their required tools. The purchase or usage of the required tools incurs a cost. The machines have scarce time and tool magazine capacities. The objective is to maximize the total weight of the assigned operations minus the total tooling costs. We use Lagrangean relaxation approach to obtain upper and lower bounds on the optimal objective function values. The computational experiments show that our approach provides near optimal bounds in reasonable solution times.     

The density based access method: A novel approach to optimizing run-time throughput for IEEE 802.11 DCF access control

According to previous work, the performance of the Distributed Coordination Function (DCF) (i.e., the basic access method of the IEEE 802.11 protocol) is far from optimum due to use of the binary exponential backoff (BEB) scheme as its collision avoidance mechanism. There has been considerable discussion of DCF issues and its performance analysis. However, most schemes assume an ideal channel, which is contrary to realistic wireless environments. In this paper, we present a simple yet pragmatic distributed algorithm, designated the density based access method (DBM), which allows stations to dynamically optimize the network throughput based on run-time measurements of the channel status. Our simulation results demonstrate that the DBM is highly accurate. The performance in terms of throughput and fairness is nearly optimal by use of the proposed scheme.     

基于粒子群优化算法的库存不确定性分析

库存不确定性问题是供应链不确定性研究的重点之一.利用粒子群优化算法快速搜寻最优解的优点对库存不确定性问题进行仿真分析,得出了库存不确定性环境下的最优解,这说明了粒子群优化算法能够辅助供应链管理者在不确定性环境下对供应链进行优化设计和决策分析.     

Numerical grid generator based on Moser's deformation method

A deformation method of grid generation has been recently proposed. The method is based on Moser's deformation scheme in his study of the volume elements of a Riemannian manifold. In this paper, this deformation method is improved so that the grid adaption takes place according to the physical coordinates. Some numerical results are included to demonstrate the method. © 1994 John Wiley & Sons, Inc.     

Observations on an adaptive moving grid method for one-dimensional systems of partial differential equations

Recently a scheme has been proposed for choosing a moving mesh based on minimizing the time rate of change of the solution in the moving coordinates for one-dimensional systems of PDEs. In this paper we show how to apply this idea to systems where the time derivatives cannot be solved for explicitly, writing the moving mesh equations in an implicit form. We give a geometrical interpretation of the scheme which exposes some of its weaknesses, and suggest some modifications based on this interpretation which increase the efficiency of the scheme. Finally, we present some numerical experiments which illustrate how well the resulting method works.     

The stochastic approach for non-Hamiltonian systems

The stochastic quantization of dissipative systems is discussed. It is shown that in order to stochastically quantize a system with dissipation, one has to restrict the Fourier transform of the space-time variable to the positive half domain in the complex plane. This breaks the time-reversal invariance, which manifests itself in the formulation through the resulting noninvariant forms for the propagators. The relation of the stochastic approach with the Caldeira and Leggett path-integral method is also analyzed.Department d'Estructura i Constituents de la Matéria, Universitat de Barcelona, E-08028 Barcelona, Spain. Published in Teoreticheskaya i Matematicheskaya Fizika, Vol. 100, No. 1, pp. 153–159, July, 1994.     

Accuracy bound of the grid method in optimal control problem for elliptic systems

A rate of convergence bound compatible with the smoothness of the solution of the original differential problem is obtained for the grid method in the optimal control problem for elliptic systems with solutions in W₂ ²(D).Translated from Vychislitel'naya i Prikladnaya Matematika, No. 61, pp. 12–19, 1987.     

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.     

An interactive decision-making approach based on intelligent systems to redraw district boundaries in regional planning

Environmental planning decisions have become a major challenge and are receiving increasing social attention. To contend with the absence of a decision theory in this domain and to solve conflicts in group decision-making, an interactive decision approach has been defined and supported by a computer-based system to automate the different steps of the modelling process. In this paper, the emphasis is on the advent of intelligent systems and the improvement of management support. This support enables individual decision-makers to augment their knowledge about a problem domain which results in a gain in productivity. The different steps of the approach are described and illustrated through a worked example which is a specific decision problem and deals with redrawing the district boundaries in regional planning.     

Parallel multiobjective evolutionary algorithms for batch scheduling in heterogeneous computing and grid systems

This article presents six parallel multiobjective evolutionary algorithms applied to solve the scheduling problem in distributed heterogeneous computing and grid systems. The studied evolutionary algorithms follow an explicit multiobjective approach to tackle the simultaneous optimization of a system-related (i.e. makespan) and a user-related (i.e. flowtime) objectives. Parallel models of the proposed methods are developed in order to efficiently solve the problem. The experimental analysis demonstrates that the proposed evolutionary algorithms are able to efficiently compute accurate results when solving standard and new large problem instances. The best of the proposed methods outperforms both deterministic scheduling heuristics and single-objective evolutionary methods previously applied to the problem.