基于遗传算法的应急物资分层联动调度研究

本文提出了在多物资、多车型特征的应急物资分层调度情况下求解调度系统中各运输工具具体调度方案的算法。该算法以系统调度任务完成时间最小为目标,基于遗传算法采用整体联动的求解思想。实际问题中的调度问题往往具有本文所提出的层次性,针对物资分层联动调度问题,本文给出了物资两层调度的算例,并建立了相应的数学模型,算例中第一层调度系统由一级仓库、二级仓库、一级运输工具和一级路网构成;第二层调度系统由灾害点、二级仓库、二级运输工具和二级路网构成,将两层调度系统视作整体,采用基于遗传算法的整体联动求解方法对算例进行求解得出结果,并对结果进行分析论证,验证算法的可行性与有效性。     

动态规划在立体仓库管理中的应用

主要围绕立体仓库内部运输工具存取路径优化问题的多种情况 ,利用动态规划做了各种数学优化模型 ,以达到提高仓库运行效率 ,从而增加企业经济效益的目的     

动态规划在立体仓库管理中的应用

主要围绕立体仓库内部运输工具存取路径优化问题的多种情况，利用动态规划做了各种数学优化模型，以达到提高仓库运行效率，从而增加企业经济效益的目的。     

夏季和冬季拖拉机的正确使用方法探讨

随着我国农村经济的快速发展,拖拉机成为农村不可或缺的运输工具,如何正确使用和保养农用拖拉机是当前广大农民朋友最关系的问题。本文详细介绍了该如何正确使用拖拉机,以及该如何对拖拉机进行保养。     

施工升降机自动控制系统设计

施工升降机是高层建筑施工中不可缺少的垂直运输工具，它主要担负着运送施工人员和施工设备及施工物料的任务。本文对施工升降机自动控制系统的原理及硬、软件进行介绍，并对控制系统的特色部分作了进一步的分析。     

APPLEⅡ到单板机的并行数据传送

开发一个单板机应用程序,通常的方法是先将编制好的单板机程序在APPLEⅡ微机上进行汇编及反汇编,然后再将经APPLEⅡ处理好的程序转移到单板机上作实际调试。而这其中的信息转移的过程,却是令应用人员感到很头痛的问题。目前采用的办法一般有两种,一是用APPLEⅡ微机将程序清单打印出来,再按照程序清单将程序手工键入单板机中,这实     

翼片式单轨气垫列车

早在50年代中期,当时还是莫斯科航空学院学生如今已是科学博士的Γ·Γ·泽利金已注意到运输工具在从200km/h(火车和汽车最高时速)到500km/h(现代飞机最低时速)速度范围之内的脱节现象.从运输工具发展史观点来看,这样的脱节现象是不应该存在的.人类最伟大的发明之一是轮子,同时又是轮子限制了陆上运输工具的速度.例如,一级方程式赛车的极限速度极少能超过300km/h.在汽车高速行驶时,轮轴会急剧发热而使轮胎脱落,离心力甚至会使轮缘断裂.当火车以300km/h速度行驶时,车轮会相对于铁轨打滑,这时车轮已无法再充分传输扭矩.因此,不少科学家和设计人员提出不用轮子而利用气垫或磁垫来取代轮子.     

单台直流电梯微计算机控制系统

作为高层建筑垂直运输工具的电梯,随着目前高层建筑的发展,对其功能及可靠性的要求也与日俱增,使研究单台电梯的微计算机控制系统具有重要价值。本文讨论了以 Intel 8080为 MPU 的微电脑控制装置,实现单台直流电梯的自动控制。     

关于热转移印花的工艺探讨及前景分析

介绍热转移印花技术的概念和优点,并通过叙述目前棉纤维热转移印花的几种方法,对棉纤维织物热转移存在的问题及前景进行了分析.     

基于知识转移的ERP实施方法与策略研究

成功的知识转移无疑是ERP成功实施的有效保证.基于此,对ERP实施过程中知识转移进行了尝试性研究.回顾了中外理论界有关ERP实施中知识转移问题的研究成果,结合知识转移和ERP的相关理论,研究了实施过程中知识转移的主要内容,分析了如何实现ERP企业内部的知识转移和ERP实施各主体之间的知识转移,影响知识转移的因素及知识转移对ERP实施成功的影响,知识转移的困难及对策,分析了ERP实施的不同阶段知识转移的侧重点.在前面的研究基础上从四个方面构建了面向ERP实施的知识转移系统的基本框架.     

Event-driven modeling of elevator assisted evacuation in ultra high-rise buildings

In the past few decades, numerous ultra high-rise buildings have been erected in the metropolitan areas of many cities around the world. For the related building designers, building occupants and the governments, fire safety problem is certainly a major concern, especially after the collapse of World Trade Center in the 9/11 event. That disaster makes people reconsider ultra high-rise building evacuation strategies. Of the current strategies, using elevators in ultra high-rise buildings to assist evacuation seems to be promising in improving evacuation efficiency. To quantitatively evaluate elevator assisted evacuation process, an event-driven agent-based modeling approach is proposed in the present paper. This modeling approach could capture not only the movement characteristics of stair-using occupants but also the detailed elevator motion features. The combined effects of occupants’ and elevators’ parameters on the evacuation efficiency have been investigated. Results indicated that the model is helpful to reveal the dynamics of elevator assisted evacuation, and sometime, using elevators to move all occupants to ground safety point may not be an optimal solution.     

An enhanced model for evacuation vulnerability assessment in urban areas

Rapid urbanization has led to a massive influx of people into cities. When many people congregate in urban areas, crowd crushing emergencies are likely to occur. If vulnerable areas with potential evacuation problems are detected in advance, crowd crushing emergencies may be minimized or even avoided. Thus, an evacuation vulnerability assessment from a precautionary perspective is fundamental. However, the current evacuation vulnerability assessment models are limited in spreading time estimation and evacuation capacity evaluation. To mitigate these limitations, in this study, we propose an enhanced model to quantitatively assess the evacuation vulnerability in urban areas. Our model enhances the current models in two ways. First, we employ a hexagon gridding scheme to construct a network to meet the prerequisite of evacuation spreading at the equal time intervals. Second, we quantify the grid connectivity on the network by considering the grid capacity to avoid underestimation of the evacuation vulnerability. Using a mobile phone location dataset of Shanghai, we systematically investigate the evacuation vulnerability of urban areas in a fine-grained spatio-temporal scale. Areas that may encounter evacuation problems to various degrees can be identified in advance. This information can support emergency management agencies in monitoring dense crowds and ensure early warnings of potential crowd crushing emergencies.     

基于深度时空Q网络的机器人疏散人群算法

针对目前人群疏散方法中机器人灵活性低、场景适应性有限与疏散效率低的问题,提出一种基于深度强化学习的机器人疏散人群算法。利用人机社会力模型模拟突发事件发生时的人群疏散状态,设计一种卷积神经网络结构提取人群疏散场景中复杂的空间特征,将传统的深度Q网络与长短期记忆网络相结合,解决机器人在学习中无法记忆长期时间信息的问题。实验结果表明,与现有基于人机社会力模型的机器人疏散人群方法相比,该算法能够提高在不同仿真场景中机器人疏散人群的效率,从而验证了算法的有效性。     

Scheduling evacuation operations

In this paper, we consider a large-scale evacuation problem after a major disaster. The evacuation is assumed to occur by means of a fleet of buses, thus leading to scheduling the evacuation operations by buses [(bus evacuation problem (BEP)]. We propose time-indexed formulations as well as heuristic algorithms such as greedy algorithms and a matheuristic. This matheuristic uses the former formulation to improve the best solution obtained by the greedy heuristics. In computational experiments, we analyze and evaluate the efficiency of the proposed solution algorithms.     

A network flow approach to a city emergency evacuation planning

Two network flow methods are presented in this paper to optimize a city emergency evacuation plan. The problem is to assign each resident of the city to one of the places of refuge (PR) in preparation for major disasters. We model the city as an undirected graph, and by solving a shortest path problem on this graph, we obtain the shortest evacuation plan. The second model takes the capacity limit on each PR explicitly into account. The problem can then be transformed into a minimal cost flow problem on a slightly modified graph. We can evaluate the efficiency of the current city evacuation plan by comparing this against the optimal solutions of the above stated problems. Also, various pieces of information obtainable from these solutions can be utilized in evaluating the current evacuation policy. In addition, sensitivity analysis can be performed to answer various what-if questions     

Integration of simulation and optimization for evacuation planning

Evacuation is a time critical process in which the highest priority is to get those people who may be affected by a disaster out of the danger zone as fast as possible. For disaster-prone areas, authorities often distribute evacuation plans well in advance, or encourage the population to prepare themselves for eventual disasters. This paper presents an approach to such planning ahead for evacuation that tightly couples optimization and traffic simulation in order to determine optimal evacuation time and exit from the area for each evacuee. In this paper, we discuss the approach’s properties and illustrate its performance using two case studies of wildfire-prone areas in the state of Victoria, Australia. The results show that our approach can lead to significant improvements when compared to ad-hoc evacuation, but these improvements also strongly depend on population density and road network topology. More generally, our research highlights the significant benefits of tightly coupling optimization and simulation for evacuation modeling.     

Efficient computation of evacuation routes on a three-dimensional geometric network

We consider a real-time emergency evacuation problem that seeks to compute a set of rapid evacuation routes in a building. Given a three-dimensional geometric structure of the evacuation network, an emergency evacuation route is a sequence of movements of people away from the threat or actual occurrence of a hazard (such as a fire, a hidden bomb) to a safe exit in the network. In such a network each room/crossing/exit in the building is designated as a node and the corridors/staircases/links between the rooms are edges. The evacuation times assigned to the edges are normally distributed random variables. This stochastic routing problem subject to deadline constraints is NP-hard. We provide a new pseudo-polynomial-time dynamic programming algorithm to solve this problem. Based on this algorithm, we construct two types of approximation algorithm, namely a fully polynomial-time approximation scheme providing “almost-optimal” solutions and a fully polynomial-time approximately feasible scheme yielding a best “almost feasible” solution. We present a case study and results of computational experiments to illustrate the working and efficacy of the proposed solution methods, respectively.     

Problems Associated with Evacuation from the Ship in Case of an Emergency Situation

The problems associated with evacuation of people from the ship in an emergency situation are analyzed, especially passenger ships are taken under consideration. The most dangerous accidents requiring evacuation are described. Marine accidents often occur as eliminating all of the hazards to human health and life is still impossible. In every case, the evacuation process from the ship must be taken under consideration. Evacuation route arrangement should provide the possibility of safe departure from danger areas for passengers and crew members. Evacuation routes designed for human interaction within the evacuation process and other important factors are reviewed. Additipnally, the method for seeking evacuation time as a function of initial distribution of passengers and evacuation routes choosing is suggested. A genetic algorithm will be used, whilst the calculated evacuation time is connected with a fitness function. Parameters of evacuation routes topology are coded as non-binary chromosomes. Genetic operators are fitted for such types of problems to avoid receiving infeasible solutions. The objective of the proposed method is to find the evacuation time in worse case scenarios.     

Branch and bound algorithms for the bus evacuation problem

The bus evacuation problem (BEP) is a vehicle routing problem that arises in emergency planning. It models the evacuation of a region from a set of collection points to a set of capacitated shelters with the help of buses, minimizing the time needed to bring the last person out of the endangered region.     

基于多智能体的森林火灾人员疏散仿真

森林火灾发生时, 对在林火蔓延过程中灾区人员疏散进行建模与仿真能够检查疏散方案是否合理, 从而为合理救灾提供指导意义. 目前对人员疏散模拟与仿真虽然有很多研究, 但对于森林火灾下人员疏散尚缺乏合适的仿真模型, 给科学救助决策带来很大困难. 为此, 提出将多智能体引入森林火灾蔓延及灾区人员疏散模型研究中, 并借助于Repast平台进行仿真, 实验结果表明本文方法能够为森林火灾人员疏散模拟与仿真提供正确的解决途径.