Sequencing the processing of incoming mail to match an outbound truck delivery schedule

This paper considers the problem of sequencing the processing of incoming mail in a processing and distribution center (P&DC) to match a given outbound truck delivery schedule. Mail arrives at a P&DC from local associate offices or remote P&DCs following an incoming schedule. The mail from an origin has different proportions to different destinations. For each destination, there are trucks scheduled with limited capacities. The objective of the problem is to determine the sequence in which the incoming mail should be processed so that the total unused truck capacity is minimized. Since, we are not concerned with detailed scheduling/routing decisions inside the P&DC, we treat the P&DC system as a single machine. Dispatching rules and heuristics are proposed for this single machine problem and tested via computational experiments. Simulation experiments are performed to test the efficiency of these methods for the original multi-center multi-machine system.     

Comparative approaches to equipment scheduling in high volume factories

Mail processing and distribution centers (P&DCs) are large factories that accept, sort, and sequence mail in preparation for delivery. A central problem in these facilities is how to schedule the equipment over the day to ensure batch production under tight equipment and workforce constraints. The problem falls into the general category of multi-level lot sizing and is notoriously difficult to solve. No exact algorithms exist that are efficient and can consistently provide high-quality solutions.     

Verification and validation meet planning and scheduling

A planning and scheduling (P&S) system takes as input a domain model and a goal, and produces a plan of actions to be executed, which will achieve the goal. A P&S system typically also offers plan execution and monitoring engines. Due to the non-deterministic nature of planning problems, it is a challenge to construct correct and reliable P&S systems, including, for example, declarative domain models. Verification and validation (V&V) techniques have been applied to address these issues. Furthermore, V&V systems have been applied to actually perform planning, and conversely, P&S systems have been applied to perform V&V of more traditional software. This article overviews some of the literature on the fruitful interaction between V&V and P&S.     

Modeling and simulation-driven development of embedded real-time systems

The design and development of embedded hard real-time (RT) systems is one of the complex development practices, because of the requirements of criticality and timeliness of these systems. One critical aspect of RT systems is the production of output before specified deadline. Formal methods are promising in dealing with the design issues of these applications, although they do not scale well for complex systems. Instead, Modeling and Simulation (M&S) provides a cost-effective approach to verify the design and implementation details of very Complex RT applications. M&S methods provide dynamic and risk-free testing environments to verify different scenarios, and they are used for feasibility analysis and verification of such systems. Nevertheless, the simulation models are usually discarded in the later phases of the development.We present the application of an M&S-based method referred to as DEVSRT (Discrete EVent System Specifications in Real-Time) to solve the discontinuity between the simulation models and the final embedded application, in this paper. DEVSRT defines explicit deadline notation for DEVS transitions, draws a clear mapping between DEVS transitions and real-time tasks and provides a formal method and tool for integration of simulation models with the associated hardware components.     

Automated composition and execution of web-based simulation systems through knowledge designing and reasoning

Modeling and simulation (M&S) techniques can be used to improve cooperation among participants by clarifying the various design aspects of a devised system. Whenever an M&S system with specific functions is required, redesigning it from scratch is time and resource intensive. Thus, an approach to reuse or reconfigure existing systems with functions similar to the required ones is a potential alternative to overcome such problems. This paper proposes a method to build composite systems providing specific M&S functions through the web. The method proposed herein offers an integrated process that includes web-based reuse of existing systems, analysis of the requirements of a composite system, derivation of the logical execution order of element systems, and interconnection of the input–output interfaces between linked constituent systems. This approach provides the required tools by dynamically reconfiguring the element systems at the requested locations. The experimental results demonstrate that the proposed procedure can provide automatic generation of the required M&S system (e.g., missile-interception simulation system) and deliver the system to the target location of the cooperative work through the web.     

A hybrid intelligent GMPPT algorithm for partial shading PV system

Maximum power extraction for PV systems under partial shading conditions (PSCs) relies on the optimal global maximum power point tracking (GMPPT) method used. This paper proposes a novel maximum power point tracking (MPPT) control method for PV system with reduced steady-state oscillation based on improved particle swarm optimization (PSO) algorithm and variable step perturb and observe (P&O) method. Firstly, the grouping idea of shuffled frog leaping algorithm (SFLA) is introduced in the basic PSO algorithm (PSO–SFLA), ensuring the differences among particles and the searching of global extremum. Furthermore, adaptive speed factor is introduced into the improved PSO to improve the convergence of the PSO–SFLA under PSCs. And then, the variable step P&O (VSP&O) method is used to track the maximum power point (MPP) accurately with the change of environment. Finally, the superiority of the proposed method over the conventional P&O method and the standard PSO method in terms of tracking speed and steady-state oscillations is highlighted by simulation results under fast variable PSCs.     

Workforce planning in a lotsizing mail processing problem

The treatment of mail objects in a mail processing centre involves many operations, in particular sorting by destination. Out of the batching problem that we can identify in such a process, there are also staff planning concerns. In this paper, we analyse a treatment area (registered mail) belonging to a mail processing center, where mail objects are treated in a chain production process. The production quantities and the transfer amounts among machines are required to be determined along the daily work period. The objective is to minimize the costs with human resources needed in the process, linked with the lotsizing production plan, by matching staff to work requirements. This leads into a lotsizing and workforce problem, for which we propose an integer programming formulation. A case study of a particular treatment area is also discussed. The formulation is adjusted to the specific constraints of this case study and some computational results are included, considering average, small and high daily amounts of mail arrived to that particular treatment area.     

Practical protocols for certified electronic mail

Electronic mail, or e-mail, has brought us a big step closer towards the vision of paperless offices. To advance even closer to this vision, however, it is essential that existing e-mail systems be enhanced with value-added services which are capable of replacing many of the human procedures established in pen and paper communications. One of the most important and desirable such services is certified e-mail delivery, in which the intended recipient will get the mail content if and only if the mail originator receives an irrefutable proof-of-delivery from the recipient. In this paper, we present the design of two third-party based certified mail protocols, termed CMP1 and CMP2. Both protocols are designed for integration into existing standard e-mail systems and both satisfy the requirements ofnonrepudiation of origin, nonrepudiation of delivery, and fairness. The difference between CMP1 and CMP2 is that the former provides no mail content confidentiality protection while the latter provides such a protection. Moreover, security of the protocols are analyzed using a recently proposed accountability framework.     

Electronic mail synergy

A brief history of messaging systems is given. The use of electronic mail in the UK is discussed and the implications for companies and their executives are described. Electronic mail is outlined in terms of a convergence between telecommunications and data processing. The market for value added networks as well as electronic mail is detailed. Software requirements for electronic mail are discussed.     

Scheduling and estimation techniques for transportation planning

The Urban Transportation Planning System (UTPS) is a computer system developed by the Urban Mass Transportation Administration for the purpose of assisting planners in the analysis of proposed mass transit systems. While UTPS provides many indicators of system performance, the estimates of operating cost have not been satisfactory. The authors have developed an alternative model for estimating the operating cost of mass transit systems. This model is designed primarily for road-based systems although both rail and road systems can be analyzed. Recognizing the relationship of operating costs with scheduling complexities, the authors also developed procedures to determine line schedules and vehicle schedules and to estimate manpower requirements for the proposed transit system. These procedures, which will be integrated in future versions of UTPS, are the subject of this paper.     

Leveraging on causal knowledge for enhancing the root cause analysis of equipment spot inspection failures

Causal correlation data over the equipment spot-inspection operation and maintenance (O&M) records and fault investigation sheets potentially reflect the state related to the causal effect of equipment failures. Various factors influence equipment failures, making it difficult to effectively analyze the main cause of the problems. Mining and leveraging these causal data from the equipment spot inspection records will undoubtedly significantly improve the root cause analysis of the fault in the O&M system. Hence, this paper introduces causal knowledge in equipment fault O&M for the first time and proposes to exploit causal knowledge for enhancing root cause analysis of equipment spot inspection failures. Specifically, an equipment fault O&M knowledge graph with causal knowledge called CausalKG is constructed to provide knowledge support for the causal analysis of faults. That is, CausalKG consists of spot-inspection knowledge graph (SIKG) and causal relationship knowledge (CRK) in equipment fault O&M. Further, a CausalKG-ALBERT knowledge reasoning model is designed. The model transforms CausalKG into network embeddings based on relational graph convolutional networks. In turn, it combines the Q&A mechanism of the language model ALBERT to mine the root cause knowledge of equipment failures. The case study confirms that incorporating the CRK is more effective than directly using the SIKG for causality reasoning; The model can fully use causal relationship knowledge to enhance the reliability of root cause analysis. This method is valuable to help engineers strengthen their causal analysis capabilities in preventive equipment maintenance.     

无线网络化控制系统的功率感知事件触发策略及其闭环稳定性

本文研究了能量受限无线网络化控制系统的设计和分析问题.首先建立了无线网络化控制系统中通信传输时的数据误码率和丢包率间的定量关系,从而在通信功率与系统性能之间建立了联系.进而设计了基于事件触发策略和功率优化机制的智能控制器,该方法充分考虑了网络节能与控制系统性能表现两方面的要求,通过添加事件触发机制减少了系统的通信次数,并在此基础上以优化算法优化单次发送功率.随后,在随机稳定框架下给出了相应闭环系统稳定的充分性条件,在理论上证明了在该充分条件下,本文的设计能够在降低通信能耗的同时令系统维持预期的性能表现.最后数值例子证明了所提出方法的有效性.     

Using simulation technique and genetic algorithm to improve the quality care of a hospital emergency department

This report shows how the quality of service at a hospital emergency department (ED) can be improved by utilizing simulation and a genetic algorithm (GA) to appropriately adjust nurses’ schedules without hiring additional staff. The simulation model is developed to cover the complete flow for the patient through the ED. The GA is then applied to find a near-optimal nurse schedule based on minimizing the patients’ queue time. The data for this research was collected from the ED of Show-Chwan Memorial Hospital in Central Taiwan. After computational analysis and comparisons, we found that by making appropriate adjustments to the nurses’ schedules, the patients’ queue time is shortened, thereby raising the quality of patient-care and patient-satisfaction.     

Autonomic resource contention‐aware scheduling

The complexity of computing systems introduces a few issues and challenges such as poor performance and high energy consumption. In this paper, we first define and model resource contention metric for high performance computing workloads as a performance metric in scheduling algorithms and systems at the highest level of resource management stack to address the main issues in computing systems. Second, we propose a novel autonomic resource contention‐aware scheduling approach architected on various layers of the resource management stack. We establish the relationship between distributed resource management layers in order to optimize resource contention metric. The simulation results confirm the novelty of our approach.Copyright © 2013 John Wiley & Sons, Ltd.     

基于容器技术的电力设备仿真云平台设计与开发

针对电力设备设计仿真流程中成本高、计算资源利用效率低等问题,利用Docker容器化技术和Kubernetes容器编排技术,构建基于容器的电力设备仿真云平台。结合仿真云平台的需求,从功能实现、镜像构建、云平台架构等方面设计云平台各模块,并对云平台运行中的关键处理流程进行分析。在此基础上,通过动态构建技术从特性匹配、调度算法等方面对云平台的运行进行优化。应用实例结果表明,基于容器的电力设备仿真云平台能充分发挥云平台的优势,正确地根据用户提供的参数应用模板进行仿真。     

Two-stage DEA: An application to major Brazilian banks

Although banking has been widely studied using standard DEA (Data Envelopment Analysis) models and its variations, these models do not in fact account for the internal structure relative to measures characterizing banking operations performance. In this paper, efficiency in Brazilian banking is measured using a two-stage process. In the first stage, called cost efficiency, number of branches and employees are used to attain a certain level of administrative and personnel expenses per year. In the second stage, called productive efficiency, these expenses allow the consecution of two important net outputs: equity and permanent assets. The network-DEA centralized efficiency model is adopted here to optimize both stages simultaneously. Results indicate that Brazilian banks are heterogeneous, with some focusing on cost efficiency and others on productive efficiency. Furthermore, cost efficiency is explained by M&A and size, while productive efficiency is explained by M&A and public status. Policy implications for the Brazilian banking sector are also derived.     

Mathematical models and solution approach for cross-training staff scheduling at call centers

Call centers face demand variations over time across multiple service categories and typically employ a cross-trained workforce with flexible schedules to hedge against these fluctuations. In practice, it is often impossible to cross-train agents in each category, thus partial and limited cross-training are the norm. This adds another layer of complexity to determine the optimal mix of cross-trained workforce (on top of the shift and tour schedules) and has created a challenging problem in the optimization of staff schedules.To solve this problem to its fullest extent, an integer program that addresses cross-training, shift schedule, days off and break assignments across multiple service categories is proposed. The model is hard to solve and a two-phase sequential approach is developed. The first phase is to find the optimal mix of the workforce, i.e., the categories to be cross-trained and the time periods in which they are to be deployed; the second phase is a smaller staff scheduling model to find the composition of the workforce and to construct their weekly tours. For all the test cases, which are of practical sizes, the two-phase sequential approach provided better solutions than the solution of the original model with a state-of-the-art commercial solver subject to imposed time limits.Experimental results with data from a call center with nine categories clearly demonstrate the significance of cross-training. In fact, partial limited cross-training, where 30% of staff is cross-trained with two skills or 10% of staff is cross-trained with three skills, could result in considerable cost savings; however, these savings could diminish quickly with the increase of efficiency loss in secondary skills. Experiments also suggest that cross-training could be a more effective approach than part-time shifts to hedge against fluctuations across service categories.     

装备采办领域复杂系统建模仿真的应用研究

在介绍复杂适应系统理论、基于Agent建模仿真方法与Repast平台的基础上,总结了利用Repast平台进行复杂系统建模仿真的一般方法。通过运用该方法,对装备采办过程中军企合作的简易模型进行了研究与实现,结合Repast平台产生的丰富的仿真数据,从如何保持军企合作竞争性的角度进行了分析,对如何提高装备采办的有效性提供了一定的数据支撑。同时,开创了运用复杂系统建模仿真方法对装备采办领域的复杂性问题进行研究的新方向。