几种电梯运行模式的比较及应用

通过对上班高峰时段的电梯运行情况进行分析,以"最后被运送的乘客的等待时间最短"的"最大最小"原则作为其评价指标,以"电梯运行周期与运行总时间之比等于电梯在一个周期内运送的乘客数与乘客总数之比"的"比例"原则为依据,对高层楼宇中人员流动高峰时段的几种电梯运行方案建立了数学模型进行描述与比较,找到了电梯停靠楼层的最佳方案,并对北京大学第三医院外科楼的运行方案做出定量的数学证明.     

一种新的基于PDF控制的电梯群控调度策略

针对电梯群控调度过程中交通特性的不确定性,建立了包括最短候梯时间,最短乘梯时间和最少能耗的电梯群控系统的模型,提出了一种适应电梯群控性能需求的伪微分反馈控制算法,并对算法进行改进来达到更好的调度效果,最后进行仿真实验.仿真结果表明该方法与其他算法相比在电梯群控调度性能和交通模式的适应性方面有较大的改善。     

考虑均衡性的不确定时间车辆调度问题研究

本文针对车辆调度实际运行过程中时间的不确定性问题,提出了包含时间窗口、车辆容量约束的配送服务线路随机规划模型,以最小化调用的车辆数目和运行距离,降低顾客的不满意度并且尽可能保证每条路线的均衡性。结合模型,给出了基于禁忌搜索的混合启发式算法,并且生成多个算例,依据算例结果说明模型和算法优越性,同时说明可以在不降低顾客满意度和不提高总运输成本的基础上,降低各条线路之间的时间差异。     

电梯决策问题的占线算法分析

结合现实生活中电梯的运营状况,从占线算法角度分析并解决了电梯运行中碰到的两个问题:乘客如何选择乘坐电梯的策略以及多少楼层以上应该开放电梯.通过对问题的描述,建立了求解模型并提出一种竞争策略;运用占线算法得到该策略的竞争比,并将此策略作为等待电梯的较优策略;通过对竞争策略的分析,并利用实地考察得到的数据,得出楼层达到4层及以上时才应该开放电梯的结论,并以此为基础对电梯运营者提出相关建议.     

网格环境下制造资源在线优化调度的区间规划模型

针对网格环境下影响制造资源优化调度的关键参数具有区间性的特点,本文基于区间数建立了在线处理模式下的资源优化调度模型,分别以任务完工的总成本最低与资源的利益最大为目标,将任务的成本限制及资源的价格转换为区间数,充分考虑了任务与资源工作时间限制,给出区间规划模型及其解法。最后通过算例分析得出该模型在反映市场需求以及快速应对市场变化基础上,可得出合理的优化调度方案,验证该方法的可行性与有效性。     

兼顾效率和成本的ARMA控制图多目标优化设计

ARMA控制图是一种有效的自相关过程质量监控方法,为了能够同时对ARMA控制图监控方案的效率和成本进行优化,本文分别研究了ARMA控制图的平均运行长度和质量成本的计算方法,并由此建立了ARMA控制图的多目标优化设计模型。采用NSGA-Ш智能优化算法,通过一个具体的算例对该模型的计算方法进行了说明,针对不同程度的过程偏移给出了多目标优化设计的非劣解解集。然后通过灵敏度分析的方法研究了模型中的主要设计参数对监控方案的效率和成本的影响程度。最后,通过与其它几种ARMA控制图优化设计方案的比较分析,说明了本文提出的设计方法的优势。     

混合无等待流水线干扰管理调度方法研究

针对带分批约束的混合无等待流水加工环境中干扰事件的出现导致初始调度计划发生偏离的问题,研究如何运用干扰管理理论来应对工件变更扰动情况,建立了兼顾最小化工件完工时间加权和指标(初始调度目标)和最小化工件完工滞后时间加权和指标(偏离校正目标)的干扰管理调度模型,提出了双层微粒群优化策略与随机多邻域搜索机制相结合的混合求解算法。数值算例仿真实验结果表明,包含“插入-交换”大概率邻域搜索算子的混合微粒群优化算法求解本文所构建的干扰管理调度模型是有效的。     

带客户协同分仓的动态车辆路径问题研究

随着互联网商业迭代的不断深化,越来越多的企业倾向于从商品前置视角解决配送距离与配送时效性的矛盾。为此,本文研究基于客户协同分仓备货的动态车辆调度问题(Dynamic Vehicle Routing Problem with Inventory Synergetic Customer, DVRP-ISC),设计考虑区域分异特征的协同分仓客户选择方法,建立多阶段动态配送网络优化模型。鉴于研究问题的特殊性,设计多阶段两级网络协同配送路径优化算法;最后,以仿真算例、自定义算例集和基准算例,验证所提模型和算法性能及其拓展性。     

模糊置换流水车间调度的多目标模型

为了求解同时考虑模糊加工时间和模糊交货期的多目标置换流水车间调度问题,提出一种模糊多目标调度模型。针对目标之一的最大化满意度,考虑决策者偏好,建立基于悲观准则的偏好满意度模型,并在此基础上,兼顾考虑可信度,对满意度模型进行改进;针对Pareto最优解的选取,引入模糊集理论和概率论,运用面积补偿法将最大模糊完工时间去模糊化,便于可行解之间进行比较。最后,采用随机系列算例以及典型算例进行优化计算,计算结果验证了模型的有效性。     

中型水库系统运行管理随机动态决策模型的研究

本文针对中型水库系统优化调度中的难点问题，提出了相应的解决方法，由此给出简单易行的系统最优运行决策模型。     

Evolutionary bi-objective optimisation in the elevator car routing problem

The paper introduces a genetic algorithms based elevator group control system utilising new approaches to multi-objective optimisation in a dynamically changing process control environment. The problem of controlling a group of elevators as well as the basic principles of the existing single-objective genetic elevator group control method are described. The foundations of the developed multi-objective approach, Evolutionary Standardised-Objective Weighted Aggregation Method, with a PI-controller operating as an interactive Decision Maker, are introduced. Their operation as a part of bi-objective genetic elevator group control is presented together with the performance results obtained from simulations concerning a high-rise office building. The results show that with this approach it is possible to regulate the service level of an elevator system, in terms of average passenger waiting time, so as to bring it to a desired level and to produce that service with minimum energy consumption. This has not been seen before in the elevator industry.     

Optimal parking of idle elevators under myopic and state-dependent policies

In this paper we discuss the problem of optimally parking single and multiple idle elevators under light-traffic conditions. The problem is analyzed from the point of view of the elevator owner whose objective is to minimize the expected total cost of parking and dispatching the elevator (which includes the cost incurred for waiting passengers). We first consider the case of a single elevator and analyze a (commonly used but suboptimal) state-independent myopic policy that always positions the idle elevator at the same floor. Building on the results obtained for the myopic policy, we then show that the optimal non-myopic (state-dependent) policy calls for dispatching the idle elevator to the state-dependent median of a weight distribution. Next, we consider the more difficult case of two elevators and develop an expression for the expected dispatching distance function. We show that the objective function for the myopic policy is non-convex. The non-myopic policy is found to be dependent on the state of the two idle elevators. We compute the optimal state-dependent policy for two elevators using the results developed for the myopic policy. Next, we examine the case of multiple elevators and provide a general recursive formula to find the expected dispatching distance functions. Finally, we generalize the previous models by incorporating a fixed cost for parking the idle elevators that results in a two-sided optimal policy with different regions. Every policy that we introduce and analyze is illustrated by an example. The paper concludes with a short summary and suggestions for future research.     

考虑释放时间的单机JIT调度问题

本文主要研究二级供应链中的生产-库存-直接配送协同调度问题,其中存在一个制造商和多个零售商, 制造商根据订单进行生产, 然后将产品配送给零售商。该类问题可以抽象为考虑释放时间的单机JIT调度问题。借助于禁忌搜索算法, 本文提出了求解问题的CTA-TS算法, 并通过大量的实验数据与已有算法进行比较,说明了本文提出算法的有效性。     

Two elevators serving up-traffic

A model is described for the motion of two elevators serving traffic only from a single lobby floor to multiple higher floors. Over a certain range of passenger arrival rates, the average round trip time of an elevator can be approximated by a linear function of the number of passengers carried which, in turn, is proportional to the time since the last elevator departure from the lobby (the headway). A pair of deterministic equations for the means of two state variables describes the approximate evolution of the system behavior. These equations lead to a very strange chaotic type of motion in the two-dimensional state space. For moderately light traffic the two elevators tend to travel close together, but for heavy traffic the headways tend to be nearly uniformly distributed over the mean round trip time of a single elevator.     

基于随机规划的建筑集群冷热电联供系统优化研究

面向建筑集群的冷热电联供系统的设计和优化是实现建筑楼宇能源成本节约的重要途径。随机因素对该联供系统的优化决策,具有显著的影响。考虑建筑楼宇的能源需求为随机变量,构建随机混合整数规划模型,解决以最小化建筑楼宇总费用为目标时建筑集群冷热电联供系统的优化问题;其次,提出采用Benders多割平面方法求解多目标规划问题,从而寻找冷热电联供系统的设备配置和系统运行的Pareto最优决策;最后,通过实验验证了模型和算法的有效性。实验结果表明建筑集群在协作模式下,相比于非协作模式,具有更低的总费用。     

Online-optimization of multi-elevator transport systems with reoptimization algorithms based on set-partitioning models

We develop and experimentally compare policies for the control of a system of k elevators with capacity one in a transport environment with ? floors, an idealized version of a pallet elevator system in a large distribution center of the Herlitz PBS AG in Falkensee. Each elevator in the idealized system has an individual waiting queue of infinite capacity. On each floor, requests arrive over time in global waiting queues of infinite capacity. The goal is to find a policy that, without any knowledge about future requests, assigns an elevator to each request and a schedule to each elevator so that certain expected cost functions (e.g., the average or the maximal flow times) are minimized. We show that a reoptimization policy for minimizing average squared waiting times can be implemented to run in real-time (1 s) using dynamic column generation. Moreover, in discrete event simulations with Poisson input it outperforms other commonly used policies like multi-server variants of greedy and nearest neighbor.     

A practical fractional numerical optimization method for designing economically and environmentally friendly super-tall buildings

Due to the complexity of super tall buildings, many well-known optimization algorithms are not well applicable. Using structural lateral system of super tall buildings as engineering background, the paper developed a practical fractional numerical optimization method (FNOM), which applies fractional strategy and quasi-constant assumption, to reduce material cost and embodied carbon cost by searching the optimal structural dimensions. Firstly, two kinds of relationships among optimization variables (structural dimensions), driven design constraints (the interstory drift and the natural period) and optimization objective (cost including material cost and embodied carbon cost) are mathematically modelled. Genetic algorithm (GA) is then introduced to search the optimal structural dimensions based on the quasi-constant assumption of virtual work and internal work of the inactive components. Thirdly, fractional strategy is applied to create assemblies composed of different structural component sets, and the assemblies are then to be optimized in proper sequences. Fourthly, FNOM is implemented as a user-friendly software called C-FNO to practically support the preliminary design of super-tall buildings. Finally, a 700 m high super-tall building is employed to illustrate FNOM by using C-FNO, and the results show that only three design constraints of the interstory drift, the natural period and the stress ratio need to be solved during each optimization step. Belt truss, mega column, outrigger truss and shear wall of the super tall building should be optimized in sequence to save more cost. A great amount of cost can be still saved for the super tall building with the normal traditional design.