微粒群算法及其在热轧生产调度中的应用

针对整数规划问题的特点,提出了一种在整数空间中进行进化计算的PSO算法,使微粒群的进化限于整数空间。给出了热轧生产调度问题的最优轧制单元数学规划模型。并将该方法成功应用于最优轧制单元求解。     

Little-Preemptive Scheduling on Unrelated Processors

We consider the preemptive scheduling of n independent jobs on m unrelated machines to minimize the makespan. Preemptive schedules with at most 2m–3 preemptions are built, which are optimal when the maximal job processing time is no more than the optimal schedule makespan. We further restrict the maximal job processing time and obtain optimal schedules with at most m–1 preemptions. This is better than the earlier known best bound of 4m ²–5m+2 on the total number of preemptions. Without the restriction on the maximal job processing time, our (2m–3)-preemptive schedules have a makespan which is no more than either of the following two magnitudes: (a) the maximum between the longest job processing time and the optimal preemptive makespan, and (b) the optimal nonpreemptive makespan. Our (m–1)-preemptive schedules might be at most twice worse than an optimal one.     

Control and scheduling in a two-station queueing network: Optimal policies and heuristics

Consider a two-station queueing network with two types of jobs: type 1 jobs visit station 1 only, while type 2 jobs visit both stations in sequence. Each station has a single server. Arrival and service processes are modeled as counting processes with controllable stochastic intensities. The problem is to control the arrival and service processes, and in particular to schedule the server in station 1 among the two job types, in order to minimize a discounted cost function over an infinite time horizon. Using a stochastic intensity control approach, we establish the optimality of a specific stationary policy, and show that its value function satisfies certain properties, which lead to a switching-curve structure. We further classify the problem into six parametric cases. Based on the structural properties of the stationary policy, we establish the optimality of some simple priority rules for three of the six cases, and develop heuristic policies for the other three cases.     

Algorithm for Scheduling Variable-Length Messages in WDM Networks

In this paper, we develop and analyze a simple algorithm for scheduling variable length messages in WDM networks with a passive star coupler. We base our schemes on a star topology with centralized control and use a scheduling algorithm similar to the process management in UNIX system. Every node and message have a scheduling priority associated with them. By comparing our algorithm with random select algorithm, we find that significant improvement in performance can be achieved with very little extra cost.     

Performance analysis of test scheduling schemes for a multi-access communications network

In this paper, we investigate the performance of two implementable test scheduling schemes for a multi-access communication channel whose components are subject to failure or malfunction. We relate the reliability of the system design, as reflected by system failure rate parameters, and the frequency at which the system (or nodal subsystem) is tested for failure detection, to the underlying key message delay and throughput performance. We derive queue-size distribution results for a discreteGeom ^(X)/D/1 system, representing the operation of the multi-access channel, or of a network node operating as a communications or queueing processor, which is maintained by a periodic or near periodic test scheduling scheme. Explicit formulas are presented for the system behavior as exhibited by the generating functions of the system queue-size distributions. The mean message delay is then calculated. The mean delay (or mean system size/workload performance index) can then be optimized by selecting the proper scheme parameters, under specified system (and component) failure conditions, noting that performing a test at too high a rate leads to inefficient system bandwidth utilization, while if tests are not carried out often enough, excessive message (or task) retransmissions and delays ensue.     

Market Power Issues in Bid-Based Hydrothermal Dispatch

The objective of this work is to investigate market power issues in bid-based hydrothermal scheduling. Initially, market power was simulated with a single stage Cournot–Nash equilibrium model. In this static model the equilibrium was calculated analytically. It was shown that the total production of N strategic agents is smaller than the least-cost solution by a factor of (N/(N+1)). Market power analysis for multiple stages was then carried through a stochastic dynamic programming scheme, where the decision in each stage and state is the Cournot–Nash equilibrium of a multi-agent game. Case studies with data taken from the Brazilian system are presented.     

面向绿色智能制造的高维多目标动态作业车间调度优化

在当前环境问题日益严峻情况下,绿色智能制造受到广泛关注。在动态柔性作业车间基础上考虑不同机器状态下的能耗情况、机器使用节能方法,构建以极小化总能耗、最大完工时间、机器总负荷和产品质量稳定性为目标的高维多目标绿色动态柔性作业车间调度模型,并设计改进的灰狼优化IMOGWO算法求解该问题。首先,采用反向学习初始化种群策略,以扩大种群多样性;然后,依据多目标问题和标准GWO算法的特点提出多级官员领导机制,并引入POX交叉和逆序变异算子;最后,改进精英保留策略用于多目标优化算法。为证明算法的有效性,设计两组仿真实验分别对三种算法进行比较。实验结果表明,运用本文改进的IMOGWO算法求解多目标问题有更好的收敛性和分布性。     

Proportional fair scheduling using water-filling technique for SC-FDMA based D2D communication

The resource allocation in SC-FDMA is constrained by the condition that multiple subchannels should be allocated to a single user only if they are adjacent. Therefore, the scheduling scheme of a D2D-cellular system that uses SC-FDMA must also conform to the so-called adjacency constraint. This paper proposes a heuristic algorithm with low computational complexity that applies proportional fair (PF) scheduling in the D2D-cellular system. The proposed algorithm consists of two main phases: (i) subchannel allocation and (ii) adjustment of data rates, which are executed for both CUEs and DUEs. In the subchannel allocation phase for CUEs (or D2D pairs), the users’ data rates are maximized via optimal power allocation to frequency-contiguous subchannels. In the second phase, a PF scheduling problem is solved to decide the modulation and coding scheme (MCS) of both CUEs and D2D pairs. Both phases of the proposed algorithm benefit from the Water-Filling (WF) technique. The simulation results suggest that the proposed scheme performs similar to optimal PF scheduling from the perspective of users’ data rate and their logarithmic sum. An additional benefit of the proposed scheme is its low computational overhead.     

Stochastic optimization of an urban rail timetable under time‐dependent and uncertain demand

Urban rail planning is extremely complex, mainly because it is a decision problem under different uncertainties. In practice, travel demand is generally uncertain, and therefore, the timetabling decisions must be based on accurate estimation. This research addresses the optimization of train timetable at public transit terminals of an urban rail in a stochastic setting. To cope with stochastic fluctuation of arrival rates, a two‐stage stochastic programming model is developed. The objective is to construct a daily train schedule that minimizes the expected waiting time of passengers. Due to the high computational cost of evaluating the expected value objective, the sample average approximation method is applied. The method provided statistical estimations of the optimality gap as well as lower and upper bounds and the associated confidence intervals. Numerical experiments are performed to evaluate the performance of the proposed model and the solution method.     

变速转子准稳态主动平衡系统的增益调度控制

在现代高速旋转机械中,不平衡引起的振动是机器性能降低甚至损坏的重要原因。对变速转子准稳态主动平衡系统,可按一定时间步长把变转速离散成有限个转动角速度。针对每个离散角速度,依据影响系数法,采用包含残余振动值和校正不平衡的广义线性二次型目标性能函数推导出控制律。通过每个离散转速下影响系数的估计和增益矩阵的计算,形成对应于各离散转速的增益表,从而实现变速转子准稳态主动平衡系统的增益调度控制。数值模拟验证了增益调度控制能很好地抑制不平衡振动。与传统的加权二乘法(WLS)相比,数值模拟显示,该法对校正不平衡的惩罚可提高系统的稳定性,也可增强控制的鲁棒性。