关于计算机数据库的弱点研究

目前,有关计算机技术已经开始研究计算机数据库的弱性问题,以发挥弱点数据库的重要作用,提高计算机系统的安全性、可靠性、机密性。分析并阐述了计算机弱点数据库的价值与原则,提出计算机弱点数据库的实现方式。     

Performance based earthquake evaluation of reinforced concrete buildings using design of experiments

Seismic resiliency of new buildings has improved over the years due to enhancements in seismic codes and design practices. However, existing buildings designed and built under earlier codes are vulnerable and require a performance-based screening and retrofit prioritization. The performance modifiers considered are soft story, weak story, and the quality of construction, which are collated through a walk down survey. The building evaluation is performed through a pushover analysis, and performance objective are obtained through initial stiffness of the pushover curve. Using a design of experiments technique, a reliable system input-output relation has been identified and used to evaluate the performance criteria at untried design points (i.e., buildings with different modifier values). The proposed method of performance based evaluation is illustrated through consideration of the different structural deficiencies on a typical six-storey reinforced concrete building in Vancouver. Through the designed experiments, the main and interaction effects of the performance modifiers have also been studied.     

Rule-based meta-heuristics for integrated scheduling of unrelated parallel machines,batches, and heterogeneous delivery trucks

In this article, we deal with an integrated scheduling for unrelated parallel machines, batches, and heterogeneous delivery trucks. In a manufacturing plant, jobs ordered by customers are manufactured by one of several unrelated parallel machines. Then, they are grouped and delivered to the respective customers by heterogeneous trucks with different capacities and travel times. The objective of the problem is to simultaneously determine the machine schedule, batching, and truck-delivery schedule to minimize the make span of the entire process. To solve this problem, we derive a mathematical model to obtain the optimal solution, and we propose rule-based meta-heuristics using single-stage GA framework. Through randomly generated instance examples, the performances of the proposed meta-heuristics are compared.     

Production planning in automotive powertrain plants: a case study

Based on a real case study from the automotive industry, this paper deals with production planning in powertrain plants. We present an overview of the production planning process and propose a mixed integer linear programme to determine the production quantities of each product over a planning horizon of several days. Then, using real data of an engine assembly line, we simulate the performance obtained through the proposed model within a rolling horizon planning process. We perform multiple tests in order to evaluate the impact of two parameters involved in this process: planning frequency and frozen horizon length. Furthermore, in order to illustrate the value of improving coordination between engine plants and their customers, we evaluate the impact of the quality of demand information (orders and forecasts). We analyse the simulation results and provide insights and recommendations in order to achieve a good trade-off between service level, inventory, and planning stability.     

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Optimal operation models for a hydropower system using partial constraint satisfaction (PCS) approaches are proposed and developed in this study. The models use mixed integer nonlinear programming (MINLP) formulations with binary variables. The models also integrate a turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream water quality impairment. New PCS-based models for hydropower optimization formulations are developed using binary and continuous evaluator functions to maximize the constraint satisfaction. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to solve the optimization formulations. Decision maker's preferences towards power production targets and water quality improvements are incorporated using partial satisfaction constraints to obtain compromise operating rules for a multi-objective reservoir operation problem dominated by conflicting goals of energy production, water quality and consumptive water uses.     

A comparison of mixed integer programming formulations of the capacitated lot-sizing problem

We propose a novel mixed integer programming formulation for the capacitated lot-sizing problem with set-up times and set-up carryover. We compare our formulation to two earlier formulations, the Classical and Modified formulations, and a more recent formulation due to Suerie and Stadtler. Extensive computational experiments show that our formulation consistently outperforms the Classical and Modified formulations in terms of CPU time and solution quality. It is competitive with the Suerie–Stadtler (S&S) formulation, but outperforms all other formulations on the most challenging instances, those with low-capacity slack and a dense jobs matrix. We show that some of the differences in the performance of these various formulations arise from their different use of binary variables to represent production or set-up states. We also show that the LP relaxation of our Novel formulation provides a tighter lower bound than that of the Modified formulation. Our experiments demonstrate that, while the S&S formulation provides a much tighter LP bound, the Novel formulation is better able to exploit the intelligence of the CPLEX solution engine.     

Maximizing the efficiency of use of nurses under uncertain surgery durations: A case study

This paper studies a nurse scheduling problem of assigning a set of nurses to surgeries scheduled on each workday in an operating room (OR) suite. This problem plays a decisive role in utilizing nurses efficiently, which is of paramount importance for OR suites to provide high-quality service at ever reduced cost. Due to significant uncertainty in surgery durations, designing schedules that achieve high nurse efficiency is complicated by the competing objective of ensuring on-time starts of surgeries. For trading off between the two performance criteria, we formulate the problem as a mixed integer programming (MIP) model with explicit probability modeling of uncertainty. We are concerned about improving nurse efficiency in terms of overtime and idle time of nurses while mastering the risk of delay of surgeries. The MIP model is applied in a large size Chinese hospital, and the results are compared with the actual performance of the OR suite. The comparisons reveal that through examining the trade-off between the performance criteria, important nurse efficiency improvements can be achieved with good on-time start performance. Moreover, the applicability of the MIP model in various problem settings is also investigated.     

OPTIMIZATION OF REDUNDANCY IN WATER DISTRIBUTION NETWORKS USING GRAPH THEORETIC PRINCIPLES

An integer goal programming based approach to maximize reliability in water distribution networks is developed. Previous work has shown that graphs which are inherently the most invulnerable to failure have the same number of links incident at each node, i.e. they are regular in degree. The converse of this statement is not true. Regular graphs can contain weaknesses such as bridges, articulation nodes, and even total disconnections. The integer goal programming formulation in this paper is combined with a procedure which recognizes both explicit and implicit articulation points within the water distribution network to ensure that such weaknesses are excluded from the final solution. The integer program component of the approach attempts to maximize regularity within the network. In the goal programming context this is achieved by minimizing the sum of the deviations, at each node, in terms of the number of links incident upon it, from the average number of links incident on a node over the whole network. The integer requirement is imposed to prevent non-integer numbers of links being selected by the model.     

Storage yard management based on flexible yard template in container terminal

With the bottleneck of port operation moving from the quay side to the yard area, storage yard management is becoming increasingly important in the container terminal. This paper studies on storage yard management in container terminal, a flexible yard template strategy is proposed instead of the fixed yard template strategy. Based on the strategy, an integrated optimization model simultaneously considering space allocation and yard crane deployment for the tactical storage yard management is formulated. Besides, Numerical experiments are conduced to verify the effectiveness of the proposed strategy and mathematical model.     

基于AHP和GIS的吕梁地区小流域山洪灾害风险区划

为准确评价山西省吕梁地区石楼县的山洪灾害风险,从山洪灾害的形成条件和流域基本情况出发,选取降雨、地形、河流水系和历史洪水四个因子为危险性评价指标;选取人口密度、耕地面积百分比和单位面积生产总值三个因子为易损性评价指标。利用层次分析法(AHP)确定各指标权重,并依托ArcGIS空间分析叠加功能得到石楼县山洪灾害危险性分布图、石楼县山洪灾害易损性分布图以及石楼县山洪灾害风险分布图。结果表明,石楼县山洪灾害风险系数最小值为0.002,最大值为0.568。低风险、中低风险、中等风险和高风险等级面积占全县面积比例分别为18.21%、26.33%、26.08%、29.38%。分析结果可为同类小流域的山洪灾害风险区划提供参考,也可为有关部门防洪减灾提供依据。