热油管道的程序设计

针对热油管道输送过程中的计算问题,应用计算机技术实现复杂计算,使用VB编程,用计算机实现热油管道的加热站数目、油输量、站间摩阻、泵站数等的计算.通过和实际数值的对比,编制的程序可以进行长输管道工艺计算,为以后相关软件的研制奠定了基础.     

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为了有效疏解城市干道交通压力,优化与实施单行交通组织是充分发挥微循环交通网络效率的重要手段。从降低干道及微循环道路饱和度的目标出发,考虑最大期望饱和度的限制要求,建立了单行交通组织优化的双层规划模型。上层规划的决策变量为支线路段的单向行车组织方案,优化目标为最小化干道路段平均饱和度和最小化干道路段饱和度超限量;下层规划在干道路段能力、支路路段能力和饱和度的限制下进行平衡配流。提出了相应的遗传算法,并通过案例对比分析了单行交通组织优化前后干道及微循环道路上的交通状况,验证了微循环道路网单行交通组织优化的效果。该模型可应用在微循环交通网络中的单行交通组织,为单行交通组织提供优化方法。     

基于0-1整数线性规划的军事空运装载优化算法

为了高效地制定军事空运装载方案,在分析空运物资和载机货舱特点的基础上,构建了6种待装物资类型模式和6种承载空间物资布局模式,将三维空运装载问题转化为二维装载问题,建立了军事空运装载问题的数学模型.通过构建空间布局转化模式,将空间布局约束转换成0-1整数线性约束,实现了对0-1整数线性规划空运装载问题的求解.仿真结果表明:该算法运算时间不超过1 s,装载方案平均载重率达38.8%,平均有效空间利用率达59.7%.     

我校学科与专业建设规划设想

分析了广州航海高等专科学校现有学科专业的体系框架和优势特色,提出了合理化学科布局,以社会需求为依据、以市场供求为导向,设置和调整相应的专业及专业方向等学科与专业建设规划原则,并阐述了强化学科建设意识、对学科和专业进行科学规划、完善学科建设管理机制等保障措施．     

C语言在嵌入式控制系统开发中的应用研究

本文分析了嵌入式控制系统的特点和嵌入式控制系统开发的过程。用C语言开发嵌入式控制系统较汇编语言开发具有优势,结合实际的开发经验,重点分析了嵌入式C语言开发中应注意的问题以及代码优化问题。     

Robust flight-to-gate assignment using flight presence probabilities

In this paper we present a novel method to improve the robustness of solutions to the Flight-to-Gate Assignment Problem (FGAP), with the aim to reduce the need for gate re-planning due to unpredicted flight schedule disturbances in the daily operations at an airport. We propose an approach in which the deterministic gate constraints are replaced by stochastic gate constraints that incorporate the inherent stochastic flight delays in such a way so as to ensure that the expected gate conflict probability of two flights assigned to the same gate at the same time does not exceed a user-specified value. The novel approach is integrated into an existing multiple time slot FGAP model that relies on a binary integer programming formulation and is tested using real-life data pertaining to Amsterdam Airport Schiphol. The results confirm that the proposed approach holds out great promise to improve the robustness of the FGAP solutions.     

Increasing the accuracy of loop detector counts using adaptive neural fuzzy inference system and genetic programming

Loop detectors are devices that are most commonly used for obtaining data at intersections. Multiple detectors are usually required to monitor a location, and this reduces the accuracy of detectors for collecting traffic volumes. The purpose of this paper is to increase the accuracy of loop detector counts using Adaptive Neural Fuzzy Inference System (ANFIS) and Genetic Programming (GP) based on detector volume and occupancy. These methods do not need microscopic analysis and are easy to employ. Four approaches for one intersection are used in a case study. Results show that the models can improve intersection detector counts significantly. Results also show that ANFIS produces more accurate counts compared to regression and GP.     

A fuzzy-stochastic optimization model for the intermodal fleet management problem of an international transportation company

ABSTRACT

In this paper, a fuzzy-stochastic optimization model is developed for an intermodal fleet management system of a large international transportation company. The proposed model integrates various strategic, tactical and operational level decisions simultaneously. Since real-life fleet planning problems may involve different types of uncertainty jointly such as randomness and fuzziness, a hybrid chance-constrained programming and fuzzy interactive resolution-based approach is employed. Therefore, stochastic import/export freight demand and fuzzy transit times, truck/trailer availabilities, the transport capacity of Ro-Ro vessels, bounds on block train services, etc. can also be taken into account concurrently. In addition to minimize overall transportation costs, optimization of total transit times and CO₂ emission values are also incorporated in order to provide sustainable fleet plans by maximizing customer satisfaction and environmental considerations. Computational results show that effective and efficient fleet plans can be produced by making use of the proposed optimization model.     

复合功率分流系统发动机起动H∞鲁棒优化控制

为改善复合功率分流混合动力系统纯电动至混合动力模式切换过程的车辆驾驶平顺性,同时确保在模型不确定和外部干扰条件下切换控制的鲁棒性,本文中提出了一种发动机起动H∞鲁棒控制策略。首先,建立复合功率分流混合动力系统动力学模型,并对纯电动至混合动力模式切换过程进行分析。其次,以车辆驾驶平顺性和发动机起动时间为优化指标,通过动态规划求解发动机最优拖转转速曲线。然后,考虑到输入轴阻尼参数摄动、驾驶员输入、道路负载、输出端转速的不确定性变化和发动机转速量测噪声的干扰,设计了发动机起动H∞鲁棒控制器。最后,通过离线仿真和台架试验对所提出的控制策略进行验证。结果表明,该策略能有效将冲击度降低至11.52 m/s^3以内,同时对模型不确定性和外部干扰有较强的抑制能力。     

灾后道路抢修和物资配送的整合优化算法

为了在有限的时间内同时获得最佳抢修效益和物资配送方案,提高救灾工作效率,针对灾后道路抢修与救灾物资配送问题,利用时空网络流动技巧,构建了两者相应的时空网络,在考虑两者的相关性后,建立了多目标的灾后道路抢修工程与紧急物资配送混合整数多重网络规划模型,提出了分解启发式求解方法。算例计算结果表明,用CPLEX数学规划软件直接求解,在求解到106.9 h时,才可求得最优解,而分解启发式方法只需31.8 min即可求得最优解,其求解效率大幅提高,求解时间对于实际的救灾工作是可以接受的。