带运力限制及单边时变约束下多出发机场航空战略投送兵力分配模型研究

利用民航力量由多个机场向一个目标机场实施航空战略投送时,由于各民航机场都具有运力限制约束,不可能无限制地快速投送兵力,因此,考虑了在多个出发机场存在运力限制约束的情况下,构建了"投送时间最短,动员机场最少"多目标决策模型,并给出了优化算法和算例.     

基于粗糙集理论的定性推理结果的约束

从分析定性推理结果存在的问题出发,提出定性约束的必要性.总结了几种现有的定性约束,提出一种新的定性约束-粗糙定性约束,利用粗糙集属性约简算法对定性推理结果进行约简.简要介绍了粗糙定性推理软件的总体设计思路流程和功能模块划分.以物资供应保障过程定性推理结果为例,对所得推理结果进行粗糙定性约束,得到重要推理结果,为物资供应保障决策提供参考意见.     

Determining crane areas for balancing workload among interfering and noninterfering cranes

This article treats the problem of subdividing an area for storing containers such that the workload is evenly shared among the cranes operating the resulting subareas. We consider two crane sets: while noncrossing constraints between cranes of the same set need to be observed, cranes of different sets do not interfere. Such a problem setting is, for instance, relevant for scheduling the (un‐)loading of vessels by parallel quay cranes operating on opposing berths or in container yards with cross‐over cranes. We formalize the resulting optimization problem, prove computational complexity, and present exact and heuristic solution procedures. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

An efficient SPH methodology for modelling mechanical characteristics of particulate composites

Particulate composites are one of the widely used materials in producing numerous state-of-the-art components in biomedical, automobile, aerospace including defence technology. Variety of modelling techniques have been adopted in the past to model mechanical behaviour of particulate composites. Due to their favourable properties, particle-based methods provide a convenient platform to model failure or fracture of these composites. Smooth particle hydrodynamics (SPH) is one of such methods which demonstrate excellent potential for modelling failure or fracture of particulate composites in a Lagrangian setting. One of the major challenges in using SPH method for modelling composite materials depends on accurate and efficient way to treat interface and boundary conditions. In this paper, a master-slave method based multi-freedom constraints is proposed to impose essential boundary conditions and interfacial displacement constraints in modelling mechanical behaviour of composite materials using SPH method. The proposed methodology enforces the above constraints more accurately and requires only smaller condition number for system stiffness matrix than the procedures based on typical penalty function approach. A minimum cut-off value-based error criteria is employed to improve the compu-tational efficiency of the proposed methodology. In addition, the proposed method is further enhanced by adopting a modified numerical interpolation scheme along the boundary to increase the accuracy and computational efficiency. The numerical examples demonstrate that the proposed master-slave approach yields better accuracy in enforcing displacement constraints and requires approximately the same computational time as that of penalty method.     

汶川地震灾后重建住房规划环境制约因素及对策

汶川特大地震发生，四川省共有153个县（市、区）不同程度受灾，全省灾区需完成城乡住房重建49131．22万m^2（445．4万套），重建城乡住房规划受到资源、环境的制约。通过对其制约因素分析，提出了对环境保护、资源保护有针对性的措施和对策，并对住房选址和建设生态人居环境提出了建议，有利于灾后重建城乡住房规划向建设生态人居环境方向发展。     

Global planning of accelerated degradation tests based on exponential dispersion degradation models

The accelerated degradation test (ADT) is an efficient tool for assessing the lifetime information of highly reliable products. However, conducting an ADT is very expensive. Therefore, how to conduct a cost-constrained ADT plan is a great challenging issue for reliability analysts. By taking the experimental cost into consideration, this paper proposes a semi-analytical procedure to determine the total sample size, testing stress levels, the measurement frequencies, and the number of measurements (within a degradation path) globally under a class of exponential dispersion degradation models. The proposed method is also extended to determine the global planning of a three-level compromise plan. The advantage of the proposed method not only provides better design insights for conducting an ADT plan, but also provides an efficient algorithm to obtain a cost-constrained ADT plan, compared with conventional optimal plans by grid search algorithms.     

Ethnic groups,political exclusion and domestic terrorism

This study examines whether the exclusion of ethnic groups from political power is an important contributing factor to domestic terrorism. To empirically test this question, we employ a negative binomial regression estimation on 130 countries during the period from 1981 to 2005. We find that countries in which certain ethnic populations are excluded from political power are significantly more likely to experience domestic terrorist attacks and to suffer from terrorist casualties; furthermore, ethnic group political exclusion is a more consistent and substantive predictor of domestic terrorist activity than general political repression or economic discrimination.     

Algorithm to solve a chance‐constrained network capacity design problem with stochastic demands and finite support

We consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real‐world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum‐cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as a foundation, our primary focus is on a chance‐constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user‐defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut‐sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 236–246, 2016     

Strategic obfuscation of production capacities

Recent supply‐chain models that study competition among capacity‐constrained producers omit the possibility of producers strategically setting wholesale prices to create uncertainty with regards to (i.e., to obfuscate) their production capacities. To shed some light on this possibility, we study strategic obfuscation in a supply‐chain model comprised of two competing producers and a retailer, where one of the producers faces a privately‐known capacity constraint. We show that capacity obfuscation can strictly increase the obfuscating producer's profit, therefore, presenting a clear incentive for such practices. Moreover, we identify conditions under which both producers' profits increase. In effect, obfuscation enables producers to tacitly collude and charge higher wholesale prices by moderating competition between producers. The retailer, in contrast, suffers a loss in profit, raises retail prices, while overall channel profits decrease. We show that the extent of capacity obfuscation is limited by its cost and by a strategic retailer's incentive to facilitate a deterrence. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 244–267, 2014     

A self‐adapting genetic algorithm for project scheduling under resource constraints

This papers deals with the classical resource‐constrained project scheduling problem (RCPSP). There, the activities of a project have to be scheduled subject to precedence and resource constraints. The objective is to minimize the makespan of the project. We propose a new heuristic called self‐adapting genetic algorithm to solve the RCPSP. The heuristic employs the well‐known activity list representation and considers two different decoding procedures. An additional gene in the representation determines which of the two decoding procedures is actually used to compute a schedule for an individual. This allows the genetic algorithm to adapt itself to the problem instance actually solved. That is, the genetic algorithm learns which of the alternative decoding procedures is the more successful one for this instance. In other words, not only the solution for the problem, but also the algorithm itself is subject to genetic optimization. Computational experiments show that the mechanism of self‐adaptation is capable to exploit the benefits of both decoding procedures. Moreover, the tests show that the proposed heuristic is among the best ones currently available for the RCPSP. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 433–448, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10029