基于改进粒子群算法V型非传统布局仓库通道优化设计

V型仓储布局是一种典型的非传统布局方式,针对V型布局主通道设计的问题,将主通道抽象为若干个点连接而成的折线通道,每条拣货通道按物动量大小对仓库进行分区,采用更加符合实际的存取货物作业的概率不相等的非完全随机存储策略,建立最小化平均拣货距离的仓库主通道设计数学优化模型。其次,设计了基于极值扰动算子的改进粒子群优化算法(EDO-PSO)进行算法求解,利用极值扰动算子解决易陷入局部最优问题,采用并行深度搜索策略,提高算法性能,并用Benchmark函数与其他改进PSO算法对比验证算法性能。最后,结合具体实验数据仿真分析,计算结果表明,该方法在相同货位分配策略下,能有效缩短总拣货距离,验证了方法的有效性。     

Integrated scheduling and batch ordering for construction project

Multi-Mode Resource Constrained Project Scheduling Problem and material batch ordering for construction project are integrated to help project manager consider various trade-offs among several costs, such as renewable resources’ cost, material price, ordering cost, back-ordering cost, inventory holding cost and reward/penalty for early/late project completion. Therefore, we prove a mixed integer programming model and impel to calculate inventory holding cost and back order cost in objective function. Moreover, a hybrid algorithm combined adapted harmony search and genetic algorithm is proposed correspondingly. In order to inherit elitist solution and maintain population’s diversity simultaneously, we add a selection operator when the harmony memory is initialized and modify the replacement operator based on distance. Besides, genetic algorithm is adopted based on a ‘012’ coding scheme. Finally, algorithm and model performance is presented and several project instances are provided with different network structures and realizations to discuss the factors on total cost.     

A multi-objective hot-rolling scheduling problem in the compact strip production

This paper addresses a hot-rolling scheduling problem from compact strip production processes. At first, a mathematical model that consists of two coupled sub-problems is presented. The first sub-problem is the sheet-strip assignment problem that is about how to assign sheet-strips to rolling-turns with the objective of minimizing virtual sheet-strips. The second is the sheet-strip sequencing problem that is about how to sort the sheet-strips in each rolling-turn with the objective of minimizing the maximal changes in thickness between adjacent sheet-strips and the change times of the thickness so as to ensure high quality sheet-strips to be produced. And then, an improved hot-rolling scheduling heuristic is proposed to solve the sheet-strip assignment problem. A multi-objective evolutionary algorithm is developed to find the Pareto optimal or near-optimal solutions for the sheet-strip sequencing problem. Besides, the problem-specific knowledge is explored. The key operators including crossover operator, mutation operator and repair operator are designed for the multi-objective evolutionary algorithm. At last, extensive experiments based on real-world instances from a compact strip production process are carried out. The results demonstrate the effectiveness of the proposed algorithms for solving the hot-rolling scheduling problem under consideration.     

Numerical approximation of the conservative Allen–Cahn equation by operator splitting method

In this paper, a second‐order fast explicit operator splitting method is proposed to solve the mass‐conserving Allen–Cahn equation with a space–time‐dependent Lagrange multiplier. The space–time‐dependent Lagrange multiplier can preserve the volume of the system and keep small features. Moreover, we analyze the discrete maximum principle and the convergence rate of the fast explicit operator splitting method. The proposed numerical scheme is of spectral accuracy in space and of second‐order accuracy in time, which greatly improves the computational efficiency. Numerical experiments are presented to confirm the accuracy, efficiency, mass conservation, and stability of the proposed method. Copyright © 2017 John Wiley & Sons, Ltd.     

Hilbert空间中二阶广义分布参数系统的反馈控制与极点配置

应用泛函分析及算子理论方法讨论了Hilbert空间中二阶广义分布参数系统的反馈控制与极点配置问题,通过构造状态反馈的具体形式使所得闭环系统实现无限多个极点的配置;利用有界线性算子的广义逆给出了问题的解及解的构造性表达式;这对广义分布参数系统的极点配置研究具有重要的理论价值.     

Structure-preserving model reduction of second-order systems by Krylov subspace methods

In this paper, structure-preserving model reduction methods for second-order systems are investigated. By introducing an appropriate parameter, the second-order system is represented by a strictly dissipative realization and the \(H_{2}\) norm of the strictly dissipative system is discussed. Then, based on the Krylov subspace techniques, two model reduction methods are proposed to reduce the order of the strictly dissipative system. Further, the reduced second-order systems are obtained. Moreover, according to the factorization of the error system, the \(H_{2}\) error bounds are represented by the Kronecker product and the vectorization operator. Finally, two numerical examples illustrate the efficiency of our methods.     

Incorporating transfer reliability into equilibrium analysis of railway passenger flow

Passenger’s transfer route choice behavior is one of the prominent research topics in the field of railway transportation. Existing traffic assignment approaches do not properly account for passenger’s expectation for transfer reliability. In this study, the transfer reliability is explicitly defined and a multi-class user equilibrium model is established, given which passengers choose the minimal-cost path based on their expected reliability thresholds. In particular, a path-based traffic assignment algorithm which combines a k-shortest path algorithm and the method of successive averages is proposed. The validity of the proposed approach is verified by an illustrative example. Using the proposed modeling approach, it is possible to determine the passenger’s collective route choice behavior based on the user equilibrium pattern. Moreover, the railway timetables can be evaluated and optimized based on the cost-based level of service estimation.     

一阶广义分布参数系统的极点配置问题

本文讨论了一阶广义分布参数系统的极点配置问题,应用算子的广义逆给出了问题的解及解的构造性表达式．     

二阶耦合广义系统的极点配置问题

讨论了Hilbert空间中二阶耦合广义系统的极点配置问题,应用算子的广义逆给出了问题的解及解的构造性表达式。     

Assignment problems with changeover cost

We consider some variant models, having changeover cost, of the assignment problem. In these models, multiple assignments to an operator are allowed. In addition to assignment costs, a changeover cost is incurred if an operator does one job after another is completed. Two different types of changeover costs and related two models are considered. Mathematical programming formulations are given for the models. When changeover costs are dependent on the operator but independent of the jobs and are non-negative, a linear programming model is obtained. For the case when changeover costs are dependent on the jobs, a linear integer programming formulation is obtained. We also show that, this problem is strongly NP-hard. A heuristic solution method is suggested for it. Numerical findings on the performance of the method are given.     

一般梯形模糊逼近算子及其在模糊运输问题中的应用

研究运输成本信息为一般模糊数的模糊运输问题.首先,在保持一般模糊数的核不变的条件下,建立一般模糊数与一般梯形模糊数的距离最小优化模型,通过求解模型得到一般模糊数的一般梯形模糊逼近算子,并给出该逼近算子具有的性质如数乘不变性、平移不变性、连续性等.然后利用该逼近算子将一般模糊运输信息表转换成一般梯形模糊运输信息表,再根据已有GFLCM和GFMDM算法得到模糊运输问题的近似最优解,最后给出具体算例分析说明方法的有效性和合理性.     

A novel elitist multiobjective optimization algorithm: Multiobjective extremal optimization

Recently, a general-purpose local-search heuristic method called extremal optimization (EO) has been successfully applied to some NP-hard combinatorial optimization problems. This paper presents an investigation on EO with its application in numerical multiobjective optimization and proposes a new novel elitist (1 + λ) multiobjective algorithm, called multiobjective extremal optimization (MOEO). In order to extend EO to solve the multiobjective optimization problems, the Pareto dominance strategy is introduced to the fitness assignment of the proposed approach. We also present a new hybrid mutation operator that enhances the exploratory capabilities of our algorithm. The proposed approach is validated using five popular benchmark functions. The simulation results indicate that the proposed approach is highly competitive with the state-of-the-art multiobjective evolutionary algorithms. Thus MOEO can be considered a good alternative to solve numerical multiobjective optimization problems.     

基于弹性区带架构的多目标设施布局问题研究

为解决设施面积不等的连续型设施布局问题,建立了基于弹性区带架构布置形式,以物料搬运成本最小、邻近关系最大、距离要求满足度最大的多目标设施布局模型。模型中考虑了区域内的横向、纵向过道,对设施的长宽比进行了限制,使得结果更符合实际情况。为克服传统多目标单一化方法需要人为设置子目标函数权重、主观性过强的缺陷,采用基于带有精英保留策略的非支配排序遗传算法(NSGA Ⅱ)的多目标优化算法求解模型,设计了相应的编码方式、交叉算子、变异算子、罚函数。最后通过某物流园区的实例分析证明了模型与方法的有效性。     

大规模定制模式下基于三角直觉模糊信息的生产指派问题研究

针对大规模定制模式下生产指派面临的模糊不确定性等问题,探讨如何运用三角直觉模糊数构建生产指派模型进而确定最满意的生产指派方案。首先,运用三角直觉模糊数刻画、设计基于顾客个性化需求与企业产出的相对偏差、产品价格与交货期等影响因素的顾客满意度函数和企业利润函数。其次,建立了兼顾企业利润和顾客满意度的调和函数,据此构建了生产指派模型,并证明该模型有可行解和最优解,然后说明模型的求解方法。最后,通过具体实例说明生产指派模型的求解过程及其有效性、合理性。     

二阶广义系统的极点配置问题(英文)

以Ｈｉｌｂｅｒｔ空间算子理论为工具讨论二阶广义分布参数系统的极点配置问题,应用算子的广义逆给出了所讨论问题的解及解的构造性表达式．     

An exponentially convergent algorithm for nonlinear differential equations in Banach spaces

An exponentially convergent approximation to the solution of a nonlinear first order differential equation with an operator coefficient in Banach space is proposed. The algorithm is based on an equivalent Volterra integral equation including the operator exponential generated by the operator coefficient. The operator exponential is represented by a Dunford-Cauchy integral along a hyperbola enveloping the spectrum of the operator coefficient, and then the integrals involved are approximated using the Chebyshev interpolation and an appropriate Sinc quadrature. Numerical examples are given which confirm theoretical results.

     

Logic programs,well-orderings and forward chaining

We investigate the construction of stable models of general propositional logic programs. We show that a forward-chaining technique, supplemented by a properly chosen safeguard can be used to construct stable models of logic programs. Moreover, the proposed method has the advantage that if a program has no stable model, the result of the construction is a stable model of a subprogram. Further, in such a case the proposed method “isolates the inconsistency” of the program, that is it points to the part of the program responsible for the inconsistency. The results of computations are called stable submodels. We prove that every stable model of a program is a stable submodel. We investigate the complexity issues associated with stable submodels. The number of steps required to construct a stable submodel is polynomial in the sum of the lengths of the rules of the program. In the infinite case the outputs of the forward chaining procedure have much simpler complexity than those for general stable models. We show how to incorporate other techniques for finding models (e.g. Fitting operator, Van Gelder-Ross-Schlipf operator) into our construction.     

A study of decision support models for online patient-to-room assignment planning

The present paper studies patient-to-room assignment planning in a dynamic context. To this end, an extension of the patient assignment (PA) problem formulation is proposed, for which two online ILP-models are developed. The first model targets the optimal assignment for newly arrived patients, whereas the second also considers future, but planned, arrivals. Both models are compared on an existing set of benchmark instances from the PA planning problem, which serves as the basic problem setting. These instances are then extended with additional parameters to study the effect of uncertainty on the patients’ length of stay, as well as the effect of the percentage of emergency patients. The results show that the second model provides better results under all conditions, while still being computationally tractable. Moreover, the results show that pro-actively transferring patients from one room to another is not necessarily beneficial.     

Novel numerical techniques for the finite moment log stable computational model for European call option

Option pricing models are often used to describe the dynamic characteristics of prices in financial markets. Unlike the classical Black–Scholes (BS) model, the finite moment log stable (FMLS) model can explain large movements of prices during small time steps. In the FMLS, the second-order spatial derivative of the BS model is replaced by a fractional operator of order α which generates an α-stable Lévy process. In this paper, we consider the finite difference method to approximate the FMLS model. We present two numerical schemes for this approximation: the implicit numerical scheme and the Crank–Nicolson scheme. We carry out convergence and stability analyses for the proposed schemes. Since the fractional operator routinely generates dense matrices which often require high computational cost and storage memory, we explore three methods for solving the approximation schemes: the Gaussian elimination method, the bi-conjugate gradient stabilized method (Bi-CGSTAB) and the fast Bi-CGSTAB (FBi-CGSTAB) in order to compare the cost of calculations. Finally, two numerical examples with exact solutions are presented where we also use extrapolation techniques to achieve higher-order convergence. The results suggest that the proposed schemes are unconditionally stable and convergent, and the FMLS model is useful for pricing options.     

图犹豫模糊Power Heronian平均算子及其在多属性决策中应用

针对需要同时考虑属性关联性及整体均衡性多属性决策问题,联合图犹豫模糊集对于不确定信息的表达优势,提出一种基于图犹豫模糊Power Heronian平均算子的多属性决策方法。首先,给出图犹豫模糊数的得分函数、精确函数及距离公式;在此基础上,提出图犹豫模糊Power Heronian平均算子和图犹豫模糊Power加权Heronian平均算子;最后,将所提算子应用于多属性决策问题中,验证所提算子的有效性和可行性。