基于动态聚簇结构的无线传感网络在海上通信中的应用

无线传感网络在海上无线通信系统中的应用越来越广泛,而受到海上环境的影响,网络的能量消耗及生命周期是衡量海上无线传感网络最重要的性能参数。传统无线传感网络的数据传输在单个节点之间进行传递,效率较低,而现有的基于簇结构的无线传感网络,把传感网络中的所有传感器节点按照一定的逻辑结构进行划分,增加了系统的传输效率。本文在研究现有的无线传感网络基础上,提出一种基于动态聚簇结构的无线传感网络,并进行仿真。     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.     

无线传感器网络安全路由协议SNEP的分析与仿真实现

以提供可靠保密通信为目标的安全路由协议的分析是无线传感器网络安全基本研究领域之一．阐述了针对无线传感器网络的攻击手段所采取的措施,研究了安全路由协议,重点研究了其中的传感网络加密协议（Sensor Network Encryption Protocol,SNEP）,并进行了仿真实现,最后针对无线传感网络的攻击方式对SNEP的安全性进行了分析．结果证明SNEP协议具有数据机密性、数据认证、防御重放攻击等安全服务．     

基于DR-System的存贮路径问题研究

本文研究的是基于DR-System的存贮路径问题,即综合考虑配送中心订货成本、配送成本、配送中心和客户库存持有成本的最小化问题．本文提出井运用启发式算法来求解谊问题．首先把问题分解为两个子问题,即配送中心的订货问题和客户的配送问题,分别求解得到问题的初始解;然后,通过分析客户配送提前对总成本的影响,来改进初始解,从而得到谊问题的一个满意解．     

基于Intergraph Smart 3D的邮轮电缆自动敷设功能优化开发

Intergraph Smart 3D软件的电缆敷设功能在化工电力行业应用较为广泛,考虑到邮轮电气生产设计中的电缆具有长度长(3 000 km～5 000 km)、种类多、通道网络复杂和分段敷设的特点,直接应用Smart 3D原生的电缆敷设功能进行电缆敷设存在较大的风险。从邮轮电缆敷设需求出发,对Smart 3D原生电缆敷设解决方案进行优化,充分考虑电气设计人员的使用习惯,基于贪心算法和单源最短路径算法(Dijkstra算法)优化算法解决断续托架的电缆敷设和电缆分区敷设最优路径选取的问题,提高电气设计人员的电缆敷设效率。     

Improving maritime inventory routing: application to a Brazilian petroleum case

The crude oil offloading and supply problem (COSP) is a type of operation maritime inventory routing (MIR) problem encountered by petroleum companies. In COSP, the company not only is responsible for the ship scheduling to carry the crude oil from production sites to discharge ports but also must maintain inventory levels at both ports (production and consumption) between safety operational bounds to avoid disruptions in its crude oil production and/or refining processes. We show how to improve significantly the decision-making process in a Brazilian petroleum company using a mixed-integer linear programming (MILP) model to represent COSP. Comparison tests with a current ship-scheduling method adopted in the company indicated that the use of the MILP model increased the transportation efficiency and reduced costs by 20% on average. In addition to the quantitative gains, the use of a MILP model to solve COSP has succeeded when encountering real-life events, such as variation in production or consumption rates, berth unavailability, and changes in the storage capacities at ports.     

Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.     

Multi-objective optimization of train routing problem combined with train scheduling on a high-speed railway network

Based on train scheduling, this paper puts forward a multi-objective optimization model for train routing on high-speed railway network, which can offer an important reference for train plan to provide a better service. The model does not only consider the average travel time of trains, but also take the energy consumption and the user satisfaction into account. Based on this model, an improved GA is designed to solve the train routing problem. The simulation results demonstrate that the accurate algorithm is suitable for a small-scale network, while the improved genetic algorithm based on train control (GATC) applies to a large-scale network. Finally, a sensitivity analysis of the parameters is performed to obtain the ideal parameters; a perturbation analysis shows that the proposed method can quickly handle the train disturbance.     

A hybrid optimization-simulation approach for robust weekly aircraft routing and retiming

We address the robust weekly aircraft routing and retiming problem, which requires determining weekly schedules for a heterogeneous fleet that maximizes the aircraft on-time performance, minimizes the total delay, and minimizes the number of delayed passengers. The fleet is required to serve a set of flights having known departure time windows while satisfying maintenance constraints. All flights are subject to random delays that may propagate through the network. We propose to solve this problem using a hybrid optimization-simulation approach based on a novel mixed-integer nonlinear programming model for the robust weekly aircraft maintenance routing problem. For this model, we provide an equivalent mixed-integer linear programming formulation that can be solved using a commercial solver. Furthermore, we describe a Monte-Carlo-based procedure for sequentially adjusting the flight departure times. We perform an extensive computational study using instances obtained from a major international airline, having up to 3387 flights and 164 aircraft, which demonstrates the efficacy of the proposed approach. Using the simulation software SimAir to assess the robustness of the solutions produced by our approach in comparison with that for the original solutions implemented by the airline, we found that on-time performance was improved by 9.8–16.0%, cumulative delay was reduced by 25.4–33.1%, and the number of delayed passengers was reduced by 8.2–51.6%.     

利用改进交叉算子的混合遗传算法求解VRPTW

设计了一种改进的混合遗传算法求解带有时间窗、有车辆重量限制的车辆优化调度问题（VRPTW），根据问题的实际情况，建立了数学模型，提出了改进的交叉算子，丰富了种群的多样性；并结合模拟退火算法的思想，对染色体的适应度适当变化，改善了传统的遗传算法容易“早熟”的缺点，加强了染色体的局部搜索能力。