A two level metaheuristic for the operating room scheduling and assignment problem

Given a surgery department comprising several specialties that share a fixed number of operating rooms and post-surgery beds, we study the joint operating room (OR) planning and advanced scheduling problem. More specifically, we consider the problem of determining, over a one week planning horizon, the allocation of OR time blocks to specialties together with the subsets of patients to be scheduled within each time block. The aim of this paper is to extend and generalize existing approaches for the joint OR planning and scheduling problem. First, by allowing schedules that include patients requiring weekend stay beds which was not the case previously. Second, by tackling simultaneously both the OR planning and patient scheduling decision levels, instead of taking them into account in successive phases. To achieve this, we exploit the inherent hierarchy between the two decision levels, i.e., the fact that the assignment decisions of OR time blocks to surgical specialties directly affect those regarding the scheduling of patients, but not the reverse. The objective function used in this study is an extension of an existing one. It seeks to optimize both patient utility (by reducing waiting time costs) and hospital utility (by reducing production costs measured in terms of the number of weekend stay beds required by the surgery planning). 0–1 linear programming formulations exploiting the stated hierarchy are proposed and used to derive a formal proof that the problem is NP-hard. A two level metaheuristic is then developed for solving the problem and its effectiveness is demonstrated through extensive numerical experiments carried out on a large set of instances based on real data.     

Optimal operation of cogeneration system coordinated by aggregator for providing the demand and supply regulation capacity

Recent growth of renewable energy generations with natural variability, such as photovoltaic generation and wind turbine generation, would make the demand and supply control in a whole power system more difficult, and therefore, alternatives for demand and supply regulation resources would be required. The authors focus on cogeneration system (CGS) as one of regulation resources. In order to procure adequate volume of regulation capability, an aggregator coordinates a number of CGSs efficiently and flexibly considering the wide variety of electricity/thermal demands of CGS owners. This paper proposes a novel optimal operation strategy of CGS coordinated by the aggregator considering the energy balance and operation cost of individual CGS owner. This paper also demonstrates the availability of CGSs for regulation capability by numerical case studies in which the actual consumption profile is employed.     

Pseudospectral method for assessing stability robustness for linear time-periodic delayed dynamical systems

The article presents a pseudospectral approach to assess the stability robustness of linear time-periodic delay systems, where periodic functions potentially present discontinuities and the delays may also periodically vary in time. The considered systems are subject to linear real-valued time-periodic uncertainties affecting the coefficient matrices, and the presented method is able to fully exploit structure and potential interdependencies among the uncertainties. The assessment of robustness relies on the computation of the pseudospectral radius of the monodromy operator, namely, the largest Floquet multiplier that the system can attain within a given range of perturbations. Instrumental to the adopted novel approach, a solver for the computation of Floquet multipliers is introduced, which results into the solution of a generalized eigenvalue problem which is linear w.r.t. (samples of) the original system matrices. We provide numerical simulations for popular applications modeled by time-periodic delay systems, such as the inverted pendulum subject to an act-and-wait controller, a single-degree-of-freedom milling model and a turning operation with spindle speed variation.     

多分量力组合加载校准装置主机结构的技术实现

主要介绍了可实现六个分量力和力矩独立或组合加载的校准装置主机结构的设计思路和具体组成。针对该装置量程宽、空间大、准确度高等特点,文章分析了装置研制过程中涉及的技术难点;围绕多分量力组合加载的实现问题,说明了多分量力组合加载的方法原理设计及加载装置主机的机械结构设计等技术问题;最后说明了校准装置实现的技术性能和试验验证情况。     

Scheduling strategy for computational-intensive data flow in generalized cluster environments

A classical problem in the field of distributed computation and parallel processing concerns reasonable allocation of resources among computational-intensive data flows. We introduce the generalized cluster in this paper for processing large-scale scientific computations and to further explore a consecutive cooperation game-based dynamic scheduling strategy. We construct an abstract generalized cluster environment and summarize the types of data flows. We then convert the multi-objective scheduling problem into a multi-objective expectation function-based continuous cooperation game model and discuss its strategy and a solution for its kernel. We also propose a dynamic scheduling mechanism to address the instability of generalized clusters to ensure a reasonable, real-time adjusting allocation scheme by monitoring and compensating appropriately. Finally, we apply our method to a real world application to demonstrate our successful scheduling strategy that achieves superior results for overall cost, cost-performance index, and mean run time when compared with other methods.     

A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs

This paper investigates a coordinated scheduling problem in a two stage supply chain where parallel-batching machine, deteriorating jobs and transportation coordination are considered simultaneously. During the production stage, jobs are processed by suppliers and there exists one parallel-batching machine in each supplier. The actual processing time of a job depends on its starting time and normal processing time. The normal processing time of a batch is equal to the largest normal processing time among all jobs in its batch. During the transportation stage, the jobs are then delivered to the manufacturer. Since suppliers are distributed in different locations, the transportation time between each supplier and the manufacturer is different. Based on some structural properties of the studied problem, an optimal algorithm for minimising makespan on a single supplier is presented. This supply chain scheduling problem is proved to be NP-hard, and a hybrid VNS-HS algorithm combining variable neighbourhood search (VNS) with harmony search (HS) is proposed to find a good solution in reasonable time. Finally, some computational experiments are conducted and the results demonstrate the effectiveness and efficiency of the proposed VNS-HS.     

航班运行系统仿真建模分析

为研究航班计划的运行效率及其在突发扰动下的鲁棒性,将计算机仿真技术应用于航空运输系统,结合分类与航班过站时间的Logistic分布拟合等,通过模拟飞机起飞/降落、滑入/滑出、过站保障和航段飞行等运行过程,建立了含有118个国内主要机场的航班运行仿真模型,在Flexsim平台上实现了大型航空公司航班计划运行仿真.此模型可以模拟正常和流控等不正常情况下的航班运行,并输出延误时间、正常率、飞机利用率、缓冲时隙等评估指标.案例分析结果表明:模型较准确地模拟了航空公司航班的实际运行情况.在正常情况下,对输出指标分析可以确定航班计划中导致延误的重点环节;在流控情况下,可以发现航班延误的范围呈扩散趋势,传播方向沿航班串向下,且延误时间逐渐减少,受直接影响航班过站时间大幅增加,受牵连影响航班过站时间减少.     

低碳环境下钢铁企业燃气系统动态平衡调度仿真

在“节能减排、降本增效”的大背景下,从碳素流视角切入,在煤气介质预测基础上,建立了0-1混合线性规划模型,以能源成本和碳交易成本总和最小化为目标,研究钢铁行业副产煤气生产调度问题。采用基于遗传算法的动态迭代调度算法,通过混合交叉算子和平均变异算子提高遗传算法局部搜索能力,并以国内某大型钢铁企业为仿真对象进行系统仿真,结果表明:混合煤气柜可以根据煤气产耗特点调整存储量,并保证存储量在合理范围内;调节用户会起到一定的缓冲作用,可以根据某种副产煤气的产耗特点响应增加或减少该种煤气的消耗量;当某种副产煤气严重不足时,固定消耗用户会根据优先级响应停调,以满足生产需求。可见副产煤气的优化调度应用可以为中国钢铁行业的低碳发展和节能减排提供技术支撑。     

A meta-heuristic optimization approach to the scheduling of bag-of-tasks applications on heterogeneous clouds with multi-level arrivals and critical jobs

As cloud computing evolves, it is becoming more and more apparent that the future of this industry lies in interconnected cloud systems where resources will be provided by multiple “Cloud” providers instead of just one. In this way, the hosts of services that are cloud-based will have access to even larger resource pools while at the same time increasing their scalability and availability by diversifying both their computing resources and the geographical locations where those resources operate from. Furthermore the increased competition between the cloud providers in conjunction with the commoditization of hardware has already led to large decreases in the cost of cloud computing and this trend is bound to continue in the future. Scientific focus in cloud computing is also headed this way with more studies on the efficient allocation of resources and effective distribution of computing tasks between those resources. This study evaluates the use of meta-heuristic optimization algorithms in the scheduling of bag-of-tasks applications in a heterogeneous cloud of clouds. The study of both local and globally arriving jobs has been considered along with the introduction of sporadically arriving critical jobs. Simulation results show that the use of these meta-heuristics can provide significant benefits in costs and performance.     

An integrated three-stage maintenance scheduling model for unrelated parallel machines with aging effect and multi-maintenance activities

We propose an integrated three-stage model for maintenance scheduling of unrelated parallel machines (UPMs) with aging effect and multi-maintenance activities (AEMMAs) using a variety of MODM techniques such as the fuzzy analytic hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), and goal programming (GP). We use fuzzy AHP in the first stage of the proposed model to account for the inherent ambiguity and vagueness in real-life maintenance scheduling problems. In the second stage, we use TOPSIS to reduce the multi-objective problem into an efficient bi-objective problem. Finally, we use GP to solve the resulting bi-objective problem and develop an optimal maintenance schedule in the third stage of the model. We use a numerical example to demonstrate the applicability of the proposed approach and exhibit the efficacy of the procedures and algorithms.