Space station short-term mission planning using ontology modelling and time iteration

This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time of the astronauts properly. A domain model is developed by using the ontology theory to describe the concepts, constraints and relations of the planning domain formally, abstractly and normatively. A method based on time iteration is adopted to solve the short-term planning problem. Meanwhile, the resolving strategies are proposed to resolve different kinds of conflicts induced by the constraints of power, heat, resource, astronaut and relationship. The proposed approach is evaluated in a test case with fifteen missions, thirteen resources and three astronauts. The results show that the developed domain ontology model is reasonable, and the time iteration method using the proposed resolving strategies can successfully obtain the plan satisfying all considered constraints.

Selection model of trip time for rural population

Referring to the 1 248 survey data of rural population in 14 provinces of China, the influencing factors of trip time choice were analyzed. Based on the basic theory of disaggregate model and its modelling method, nine grades were selected as the alternatives of trip time, the variables affecting time choice and the method getting their values were determined, and a multinomial logit (MNL) model was developed. Another 1 200 trip data of rural population were selected to testify the model's validity. The result shows that the maximum absolute error of each period between calculated value and statistic is 3.6%, so MNL model has high calculation accuracy.

Optimum design of equivalent accelerated life testing plans based on proportional hazards-proportional odds model

The optimum design of equivalent accelerated life testing plan based on proportional hazards-proportional odds model using D-optimality is presented. The defined equivalent test plan is the test plan that has the same value of the determinant of Fisher information matrix. The equivalent test plan of step stress accelerated life testing （SSALT） to a baseline optimum constant stress accelerated life testing （CSALT） plan is obtained by adjusting the censoring time of SSALT and solving the optimization problem for each case to achieve the same value of the determinant of Fisher information matrix as in the baseline optimum CSALT plan. Numer- ical examples are given finally which demonstrate the equivalent SSALT plan to the baseline optimum CSALT plan reduces almost half of the test time while achieving approximately the same estimation errors of model parameters.

A STEP Based Integrated System for Assembly Planning and Design

An integrated system for assembly planning and design (INSAPS) is presented in which product data can be exchanged between assembly planning and assembly design on the basis of standard for exchange of product data model (STEP). The system consists of CAD system, product modeling system, assembly planning system. The product model is organized according to the STEP, uses mostly the entities of IR (integrated resources) and partly self defined entities which is necessary for assembly planning. A simple method of assembly sequence generation is presented which is suitable for complex assembly planning. The generated assembly sequences are evaluated considering the optimization of total assembly time. The results of assembly planning are feedback to the stage of assembly design to improve design.

Tour Planning for Sightseeing with Time-Dependent Satisfactions of Activities and Traveling Times

This paper proposes a new personal tour planning problem with time-dependent satisfactions, traveling and activity duration times for sightseeing. It is difficult to represent the time-dependent model using general static network models, and hence, Time-Expanded Network (TEN) is introduced. The TEN contains a copy to the set of nodes in the underlying static network for each discrete time step, and it turns the problem of determining an optimal flow over time into a classical static network flow problem. Using the proposed TEN-based model, it is possible not only to construct various variations with time of costs and satisfactions flexibly in a single network, but also to select optimal departure places and accommodations according to the tour route with tourist’s favorite places and to obtain the time scheduling of tour route, simultaneously. The proposed model is formulated as a 0 - 1 integer programming problem which can be applied by existing useful combinatorial optimization and soft computing algorithms. It’s also equivalently transformed into several existing tour planning problems using some natural assumptions. Furthermore, comparing the proposed model with some previous models using a numerical example with time-dependent parameters, both the similarity of these models in the static network and the advantage of the proposed TEN-based model are obtained.

Marginal Expansion Planning of Infrastructure at a Container Terminal

Globalization push container terminal grown rapidly in decade. To fulfill the future traffic requirement, this study highlights marginal expansion planning of infrastructure in a container terminal. By using marginal approach, the expansion plan can be determine correctly and economically stage by stage. A mathematical model has generated to calculate the expansion size, expansion time, interval of expansion, expansion cost, and significant of expansion for each infrastructure respectively. It recommended determining the expansion plan for each infrastructure respectively. This is because one of the infrastructures needs to be expanding but the other may not. The generated model was verified with others model and validated with case study to investigate the practicability of the model. The model serves as expansion decision making tools to assist port expansion planners.

基于STEP的面向对象工艺计划信息模型

工艺计划信息的表达方式直接影响ＣＡＰＰ系统与ＣＩＭ环境下其它分系统之间的信息交换。本文在分析工艺计划信息模型研究现状的基础上，从应用需求出发，提出了将实用性与通用性相结合的工艺计划信息建模策略。基于该策略，提出了面向对象的分层工艺计划信息表达方式，并建立了相应的ＥＸＰＲＥＳＳ模型。最后介绍了ＥＸＰＲＥＳＳ模型向底层实现机制转换的两种方式。

Calculation of Taper Rolling Time in Plan View Pattern Control Process

The forward slip model with adhesion was used to derive the formula of calculating taper rolling time. The relation between the rolling time and the taper length and the relation between the rolling time and the taper thickness can be obtained. The numerical solution for this formula was used on site. According to the simulation result, the roll gap value should be changed linearly with rolling time.

面向STEP-NC的特征CAD/CAPP系统

将特征建模技术与STEP及STEP-NC标准相结合,为实现CAD/CAPP/CAM及CNC的集成,探索了一条有效的途径。建立基于STEP AP224的特征模型,它包含工艺设计所需要的产品管理、材料、精度等信息。另外,将特征与加工方法链相对应,并建立相应的数据库,同时讨论了工步排序的若干规则。在Pro/ENGINEER软件平台上,实现了CAD/CAPP/CAM高层次的集成。以三轴数控加工的棱柱体零件为例,阐述了工步的产生以及排序,最终生成符合STEP-NC标准的加工文件。

基于STEP的零件加工工艺计划模型

为了满足ＣＩＭＳ环境下工艺设计系统与其它系统集成的需要，建立标准工艺计划模型具有十分重要的意义。本文描述了一个基于ＳＴＥＰ的零件加工工艺计划模型，介绍了建立这一模型的关键技术，给出了参照ＳＴＥＰ建立工艺计划模型的方法。

Data analytics approach for travel time reliability pattern analysis and prediction

Travel time reliability(TTR)is an important measure which has been widely used to represent the traffic conditions on freeways.The objective of this study is to develop a systematic approach to analyzing TTR on roadway segments along a corridor.A case study is conducted to illustrate the TTR patterns using vehicle probe data collected on a freeway corridor in Charlotte,North Carolina.A number of influential factors are considered when analyzing TTR,which include,but are not limited to,time of day,day of week,year,and segment location.A time series model is developed and used to predict the TTR.Numerical results clearly indicate the uniqueness of TTR patterns under each case and under different days of week and weather conditions.The research results can provide insightful and objective information on the traffic conditions along freeway segments,and the developed data-driven models can be used to objectively predict the future TTRs,and thus to help transportation planners make informed decisions.

Optimization of Manufacturing Supply Chain with Stochastic Demand and Planned Delivery Time

In this paper, a manufacturing supply chain system composed by a single-product machine, a buffer and a stochastic demand is considered. A stochastic fluid model is adopted to describe the system and to take into account stochastic delivery times. The objective of this paper is to evaluate the optimal buffer level used in hedging point policy taken into account planned delivery times, machine failures and random demands. This optimal buffer allows minimizing the sum of inventory, transportation, lost sales and late delivery costs. Infinitesimal perturbation analysis method is used for optimizing the proposed system. Using the stochastic fluid model, the trajectories of buffer level are studied and the infinitesimal perturbation analysis estimators are evaluated. These estimators are shown to be unbiased and then they are implanted in an optimization algorithm, which determines the optimal buffer level in the presence of planned delivery time. Also in this work, we discuss the advantage of the use of the infinitesimal perturbation analysis method comparing to classical simulation methods.

运用STEP实现PDM与ERP的集成

分析了PDM系统与ERP系统之间需要集成的主要内容,引入了STEP数据交换技术,论述了目前几种常见的PDM/ERP系统集成模式的优缺点以及适用情况.结合南阳石油机械厂企业信息化建设中的实际情况,提出了运用STEP技术实现PDM与ERP系统集成的方案,并给出了集成模型.

基于STEP的回转叶片体的曲面路径规划算法研究

近年来,随着五轴加工技术的发展,对数控软件路径生成功能提出了更高的要求,尤其是对自由曲面加工的刀具路径规划方面。文章基于STEP格式的回转叶片模型,利用Ultimate Eyeshot实现回转体的目标特征信息提取并进行曲面路径规划。本算法研究为回转叶片模型的增材制造提供了新方法,对自由曲面加工具有借鉴意义。

双延迟深度确定性策略的AUV路径规划控制

为了在复杂未知环境中提升水下机器人的实时控制精度,提出一种基于双延迟深度确定性策略的水下机器人路径规划控制方法。在没有环境先验知识的情况下,通过在线测量使用双延迟深度确定性策略算法计算水下无人机的连续控制输入。考虑洋流随机高斯模型,引入一种综合奖励函数,并且提出一种基于阶跃强化学习的六自由度动力学水下无人机自适应运动规划和避障技术。仿真结果表明提出方法能够有效实现位置环境下的高精度实时控制,并且具有一定的泛化能力。

PLANNED LEAD TIME OPTIMIZATION IN MATERIAL REQUIREMENT PLANNING ENVIRONMENT FOR MULTILEVEL PRODUCTION SYSTEMS

This paper deals with the problem of planned lead time calculation in a Material Requirement Planning （MRP） environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging costs. The proposed approach is based on discrete time inventory control where the decision variables are integer. Two types of systems are considered： multi-level serial-production and assembly systems. For the serial production systems （one type of component at each level）, a mathematical model is suggested. Then, it is proven that this model is equivalent to the well known discrete Newsboy Model. This directly provides the optimal values for the planned lead times. For multilevel assembly systems, a dedicated model is proposed and some properties of the decision variables and objective function are proven. These properties are used to calculate lower and upper limits on the decision variables and lower and upper bounds on the objective function. The obtained limits and bounds open the possibility to develop an efficient optimization algorithm using, for example, a Branch and Bound approach. The paper presents the proposed models in detail with corresponding proofs and se＇~eral numerical examples. Some advantages of the suggested models and perspectives of this research are discussed.

一种融合改进A^(*)算法与改进动态窗口法的文旅服务机器人路径规划

为满足复杂环境下文旅服务机器人路径规划算法搜索的导向性、静态环境下全局路径的最优性和动态环境下实时避障的安全性的需要,提出了一种基于改进A^(*)算法与动态窗口法相融合的算法。首先,在传统A^(*)算法的基础上,采用更精确的搜索邻域选取策略,并引入障碍物占用栅格率来量化地图信息,动态调节启发函数和权重系数;其次,引入安全距离概念,提出一种三次折线优化方法,剔除冗余节点和拐点,以提高路径的平滑性;针对狭窄通道环境,提出一种自适应圆弧优化方法,使路径更符合机器人的运动学约束。通过加入动态障碍物垂直距离代价函数,有效减少机器人与动态障碍物的冲突和碰撞风险;最后,将改进A^(*)算法与动态窗口法相融合,选取关键路径点作为动态窗口法的临时目标点,分段使用动态窗口法进行局部实时路径修正。实验结果表明,该融合算法同时具备搜索导向性、全局路径最优性和动态避障能力,能够安全快速到达目标点,具有一定的应用价值。

基于BIM和改进RRT算法的建筑机器人路径规划

针对建筑机器人在施工现场获取地图信息时间长且需要规划出一条全局的、能实时避障的路径等问题,该文提出了一种应用建筑信息模型(building information model,BIM)技术建立导航地图并进行路径规划的算法。根据BIM模型中的信息对传统RRT算法进行优化改进,提出了IRRT(improved rapid-exploration random tree)算法。首先将原有的固定步长改为动态步长,通过判断与目标点的远近界定步长大小,避免了节点的盲目扩张;其次,对随机采样点的生成范围进行了约束,并设置一个同时考虑目标点和随机点的权重来解决传统RRT算法中新生成点仅由随机采样点单一决定的问题;算法陷入最小值时选取随机扰动策略进行逃脱;最后在全局路径的相邻节点间使用动态窗口法进行局部避障。实验仿真结果表明IRRT算法比传统RRT算法在搜索速度上快了3倍多,平均路径比改进前减少25.56%,平均节点减少8.92%,加入动态窗口法后有效提高了机器人实时避障能力,更适合多变的室内环境使用。

基于按需比例分配机制的风光火氢多时间尺度协同规划

随着高比例新能源新型电力系统的灵活性需求增加,制定灵活性资源市场运营机制实时平衡大规模新能源出力波动性和不确定性十分重要。为此,文中提出一种基于按需比例分配机制的风光火氢协同规划方法。首先,制定风/光场站和氢储能系统的三阶段协调运行策略,根据按需比例分配机制进行风/光场站间功率交易,协调风电场和光伏电站的收益和支出,由火电和氢储能系统提供运行灵活性,采用固定利润比例模型保证氢储能系统的收益稳定性;然后,综合考虑投资决策和运行模拟,将功率交易成本和灵活性资源调节成本纳入优化目标,建立以风光为主体电源,以火电和氢储能为辅助电源的多时间尺度协调规划模型;最后,以中国东北某省级电网为算例进行分析。结果表明,采用文中所提方法进行电源规划可以兼顾经济性和环保性,降低灵活性资源需求和投资成本,提高风/光场站的功率利用率。

基于改进遗传算法的印刷车间多AGV调度研究

针对当前印刷车间内印刷品依赖人工搬运、AGV利用率低且多AGV作业时会发生碰撞、死锁等问题,本研究提出了一种改进的遗传算法对AGV的任务分配进行优化。首先,结合印刷车间的实际环境,以AGV搬运任务总时间最少作为目标函数进行建模;其次,利用加入了时间窗模型的改进双向A*算法对传统遗传算法进行优化,实现AGV的路径规划与调度管理;最后,利用MATLAB仿真软件对该算法进行仿真验证。对比传统遗传算法与改进遗传算法仿真结果,发现改进后的遗传算法得到的AGV调度结果搬运任务用时比传统遗传算法节省了13%,迭代次数比传统遗传算法减少了42%,因此改进后的遗传算法能更好的实现印刷车间内多AGV的无碰撞运行、路径规划与调度。