Modeling discrete event scalable network systems

Scalability in simulation tools is one of the most important traits to measure performance of software. The reason is that today’s Internet is the main instance of a large-scale and highly complex system. Simulation of Internet-scale network systems has to be supported by any simulation tool. Despite this fact, many network simulators lacks support for building large models. In this work, in order to propose a new approach for scalability issue in network simulation tools, a network simulator is developed based on behavior of honeybees and high performance DEVS, modular and hierarchical system theoretic approach. A biologically-inspired discrete event modeling approach is described for studying networks’ scalability and performance traits. Since natural systems can offer important concepts for modeling network systems, key adaptive and emergent attributes of honeybees and their societal properties are incorporated into a set of simulation models that are developed using the discrete event system specification approach. Large-scale network models are simulated and evaluated to show the benefits of nature-inspired network models.     

一种简化的NS2链路模型

基于离散事件模拟技术的NS2网络模拟器被广泛运用于计算机网络的研究中。传统的NS2链路模型复杂度高,导致了大规模网络模拟由于需要大量的计算时间而难以实现。为降低网络模拟所需要的计算开销,以提高网络模拟的规模以及性能,提出一种简化的NS2链路模型。与传统的NS2链路模型相比,该模型在不影响网络模拟真实性的前提下,不再在链路模型中维护分组缓存队列,并将部分离散事件采用直接计算来处理,以减少离散事件个数,降低模拟运行时间。实验表明,该模型在保证真实性的前提下,使模拟运行时间减少35%以上。     

Supply chain network equilibrium with revenue sharing contract under demand disruptions

Contract is a common and effective mechanism for supply chain coordination, which has been studied extensively in recent years. For a supply chain network model, contracts can be used to coordinate it because it is too ideal to obtain the network equilibrium state in practical market competition. In order to achieve equilibrium, we introduce revenue sharing contract into a supply chain network equilibrium model with random demand in this paper. Then, we investigate the influence on this network equilibrium state from demand disruptions caused by unexpected emergencies. When demand disruptions happen, the supply chain network equilibrium state will be broken and change to a new one, so the decision makers need to adjust the contract parameters to achieve the new coordinated state through bargaining. Finally, a numerical example with a sudden demand increase as a result of emergent event is provided for illustrative purposes.     

基于O-D矩阵估计的路网交通流量仿真模型

为了将交通出行需求对路网交通流量的影响进行动态的量化分析,提出了一个基于O-D矩阵估计的路网交通流量仿真模型。利用O-D矩阵估计的重力模型计算方法、复杂网络理论和路段阻抗模型,构建了路网模型;在人们出行总是选择路段阻抗最小路径的假定下,设计了出行需求的路网流量映射算法;基于离散事件仿真,在PC系统上实现了路网流量仿真系统。仿真结果表明：该仿真系统可以根据各交通子区域出行需求的变化,精确模拟路网流量和交通状态的动态演进。     

Static timing analysis for modeling QoS in networks-on-chip

Networks-on-chip (NoCs) are used in a growing number of SoCs and multi-core processors. Because messages compete for the NoC’s shared resources, quality of service and resource allocation are major concerns for system designers. In particular, a model for the properties of packet delivery through the network is desirable. We present a methodology for packet-level static timing analysis in NoCs. Our methodology quickly and accurately gauges the performance parameters of a virtual-channel wormhole NoC without simulation. The network model can handle any topology, link capacities, and buffer sizes. It provides per-flow delay analysis that is orders-of-magnitude faster than simulation while being significantly more accurate than prior static modeling techniques. Using a carefully derived and reduced Markov chain, the model can statically represent the dynamic network state. Usage of the model in a placement optimization problem is shown as an example application.     

具有模糊需求的多商品流供应链网络均衡研究

研究由多个相互竞争的制造商与多个相互竞争的零售商组成,且零售商处面临模糊市场需求、存在差异性的多商品供应链网络均衡问题.运用logit模型刻画消费者的随机选择行为,利用模糊事件的可信性测度推导零售商的模糊期望利润,借助有限维变分不等式理论构建具有模糊需求的多商品流供应链网络均衡状态满足的变分不等式,并分析了供应链网络均衡解的存在性和唯一性.最后,结合算例讨论了需求的模糊性对供应链网络均衡的影响.     

Optimization of carsharing fleet size to maximize the number of clients served

Carsharing services aim at offering short-term car rentals. Those rentals can be offered in different modalities, such as round-trip and one-way. This work simulates the dynamics of possible carsharing clients searching for resources availability and using the carsharing service. Clients can rent a vehicle if there is an available car at the client's origin station and an available parking slot at the client's destination station. If there is no car or parking slot available, the possible clients look for these resources in other stations nearby their origin and destination. Together with this Agent-Based simulation, the fleet of vehicles is optimized to serve as many clients as possible and to avoid wasting resources. This work proposes a Mixed-Integer Linear Programming Model to optimize the fleet size of a carsharing service for the one-way and round-trip modes while simulating the clients interaction. Different scenarios are analyzed using real parameters and spatial data from the city of São Paulo, Brazil. Those scenarios are composed for round-trip and one-way, varying the number of possible clients, the maximum number of available vehicles, different sets of carsharing stations and the corresponding number of parking slots. We also explore the distance walked by clients to find an available vehicle to rent or a parking slot to deliver the rented vehicle. The Agent-Based simulation showed that clients' flexibility to walk was well aligned with a higher allocation of vehicles in the same station, since it increased the possibility of sharing cars among nearby clients. Also, results show that round-trip services can scale-up better than one-way services, and that distances walked by the clients to be served are essential to make the most of the one-way mode's vehicles and parking slots.     

Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks

This paper addresses a bi-modal multi-objective discrete urban road network design problem with automobile and bus flow interaction. The problem considers the concurrent urban road and bus network design in which the authorities play a major role in designing bus network topology. The road network design deals with the decision making for new street constructions, lane additions to existing streets, lane allocations for two-way streets, and the orientations and locations of one-way streets. The bus network design is performed by keeping the terminal stations of the existing bus lines unchanged and redesigning the forth and back routes of each line. Four measures, namely user benefit, the demand coverage of the bus network, the demand share of the bus mode, and the average travel generalized cost of bus passengers, are used to evaluate the network design scenarios. The problem is formulated as a multi-objective optimization model in which a modal-split/assignment model is included to depict the mode and route choice behaviors of travelers. The model is solved by the hybrid genetic algorithm and the hybrid clonal selection algorithm. The performance of these algorithms is presented and investigated by solving a number of test networks.     

Using simulation for facility design: A case study

A discrete event simulation model was developed and used to estimate the storage area required for a proposed overseas textile manufacturing facility. It was found that the simulation was able to achieve this because of its ability to both store attribute values and to show queuing levels at an individual product level. It was also found that the process of undertaking the simulation project initiated useful discussions regarding the operation of the facility. Discrete event simulation is shown to be much more than an exercise in quantitative analysis of results and an important task of the simulation project manager is to initiate a debate among decision makers regarding the assumptions of how the system operates.     

基于直觉模糊熵的专家权重确定方法及其验证

针对专家判断信息以直觉模糊集给出的直觉模糊群决策矩阵,提出一种新的客观确定专家权重的方法。与传统的通过专家评价的差异程度来确定专家权重的思路不同,该方法通过定义直觉模糊集的模糊熵计算专家判断信息的模糊程度,进而确定每位专家的权重,并对基于犹豫度、几何距离、相似度量和不确定程度4类模糊熵的定义对专家权重结果的影响进行实验和仿真分析。仿真结果表明,专家的权重不仅取决于不同类模糊熵的定义,还与专家个数和属性个数相关。     

具有风险规避型零售商的闭环供应链网络均衡分析

在随机需求条件下研究了由多个相互竞争的供应商、制造商、零售商和消费市场组成,且零售商具有风险规避特性的再制造闭环供应链网络均衡问题.通过对不同决策层级最优化行为的分析,分别得到各层级和整个供应链网络实现均衡的条件,并建立相关的变分不等式模型.运用拟牛顿算法对变分不等式进行求解,通过仿真分析了随机再制造率和零售商的风险规避程度对网络成员最优行为和闭环供应链网络均衡的影响.     

Modelling adaptive multi-agent manufacturing control with discrete event system formalism

This paper introduces an approach for modelling and designing multi-agent control architectures for agile manufacturing using a generic formalism based on a system-theoretic discrete event approach. To describe the details of the modelling strategy, we apply the proposed approach to a multi-agent network for Job flow control in a manufacturing plant. Two interacting types of autonomous controllers, Part Agents and Machine Agents, are in charge of controlling the part flow and the machine processing sequences. Both type of agents are first modelled as atomic discrete event systems and subsequently integrated in the model of the entire network of autonomous controllers. To improve the performance of the network of agents, we introduce a mechanism based on evolutionary algorithms adapting the agents’ decision laws that are encapsulated in agents’ states. Through network simulation, the algorithm continuously searches for effective decision laws, consequently adapting agent's behaviour to the current operational conditions of the manufacturing floor. Simulation results show the potentialities of the approach.     

低碳供应链生态研发、合作促销与定价的微分博弈分析

针对低碳供应链研发、促销与定价问题, 构建微分博弈模型. 将产品低碳度和商誉作为状态变量, 综合考虑价格和非价格因素对市场需求的多重影响, 考察并比较不同决策下供应链的反馈均衡策略, 结合数值模拟, 对相关参数进行敏感性分析. 研究发现: 集中式决策可促使供应链实现经济绩效和环境绩效双赢; 产品批发价对分散式决策下供应链均衡策略及利润产生重要且不同影响; 两种决策下产品低碳度随时间单调变化, 而商誉的变化却呈现多样性.

     

新零售下生鲜产品闭环物流网络模糊规划

针对我国新零售模式的快速发展，消费者对生鲜产品需求与退货的模糊不确定性问题，考虑最低物流总成本、最佳设施选址以及最优配送车辆运输路径的决策，构建了新零售下生鲜产品闭环物流网络模糊规划模型。为求解该模型，将需求量与退货量看成三角模糊参数，利用模糊机会约束方法将模糊约束转化为等价的清晰条件。以上海市某生鲜电商企业为实例，通过置信水平的敏感性分析以及遗传算法与粒子群算法的双求解，验证了模型的有效性与可行性，进而为相关决策者提供了借鉴。     

具有损失规避零售商的模糊供应链网络均衡

针对模糊市场需求情形,研究具有损失规避行为零售商的无缺货成本的供应链网络均衡问题。利用模糊事件的可信性测度理论,推导具有分段线性效用函数损失规避零售商的模糊期望效用模型,揭示其凹性性质。利用变分不等式理论,描述制造商、零售商和消费者的最优行为,进而构建网络均衡模型。为了简化网络均衡条件,揭示了制造商与零售商内生交易定价机制的等价关系。最后,利用数值分析表明了市场需求的模糊性和损失规避系数对网络均衡的影响。     

Ptolemy离散事件模型形式化验证方法

Ptolemy是一个广泛应用于信息物理融合系统的建模和仿真工具包,主要通过仿真的方式保证所建模型的正确性.形式化方法是保证系统正确性的重要方法之一.本文提出了一种基于形式模型转换的方法来验证离散事件模型的正确性.离散事件模型根据不同事件的时间戳触发组件,时间自动机模型能够表达这个特征,因此选用Uppaal作为验证工具.首先定义了离散事件模型的形式语义,其次设计了一组从离散事件模型到时间自动机的映射规则.然后在Ptolemy环境中实现了一个插件,可以自动将离散事件模型转换为时间自动机模型,并通过调用Uppaal验证内核完成验证.最后以一个交通信号灯控制系统为例进行了成功的转换和验证,实验结果证实了该方法能够验证Ptolemy离散事件模型的正确性.     

Coordination policies to support decision making in distributed production planning

Distributed production networks are considered organizational structures able to match agility and efficiency necessary to compete in the global market. Performances of such organization structures heavily depend on the ability of the network actors of coordinating their activities. The research proposes to model and design coordination problems within production network by using the Multiple Agent Technology. In particular, the paper proposes new strategies for coordinating production-planning activities within production networks. Such models have been developed and tested by using a proper simulation environment developed by using open source code and architecture.

The results of the research can be located at two levels: (a) concerning the specific coordination problem addressed, the research provides some insights to make decisions about the choice of coordination approaches to be used in distributed production planning problems; (b) at more strategic level, the paper shows how Agent Technology and discrete event simulation can be used to build up efficient coordination structures for production networks.     

A Nash equilibrium simulation model for the competitiveness evaluation of the auction based day ahead electricity market

This paper presents a simulation model based on the Nash equilibrium notion for the auction based day ahead electricity generation market. The presented model enhances a previous formalism proposed in the related literature by employing empirical data distributions of the market clearing price as registered by the market authority (e.g. the Independent System Operator). The model is effective when power suppliers with different generation capacities are considered, differently from the starting model that unrealistically assumes equal capacities. The proposed approach aims at evaluating the electricity market competitiveness with regard to the bidder strategies in order to prevent their anticompetitive actions. The framework is applied to a real data set regarding the Italian electricity market to enlighten its effectiveness in different scenarios, varying the number and capacity of participating bidders. The model can be employed as a basis for a decision support tool both for market participants (to define their optimal bidding strategy) and regulators (to avoid collusive strategies).     

Context-prediction performance by a dynamic Bayesian network: Emphasis on location prediction in ubiquitous decision support environment

Ubiquitous decision support systems require more intelligent mechanism in which more timely and accurate decision support is available. However, conventional context-aware systems, which have been popular in the ubiquitous decision support systems field, cannot provide such agile and proactive decision support. To fill this research void, this paper proposes a new concept of context prediction mechanism by which the ubiquitous decision support devices are able to predict users’ future contexts in advance, and provide more timely and proactive decision support that users would be satisfied much more. Especially, location prediction is useful because ubiquitous decision support systems could dynamically adapt their decision support contents for a user based on a user’s future location. In this sense, as an alternative for the inference engine mechanism to be used in the ubiquitous decision support systems capable of context-prediction, we propose an inductive approach to recognizing a user’s location by learning a dynamic Bayesian network model. The dynamic Bayesian network model has been evaluated with a set of contextual data from undergraduate students. The evaluation result suggests that a dynamic Bayesian network model offers significant predictive power in the location prediction. Besides, we found that the dynamic Bayesian network model has a great potential for the future types of ubiquitous decision support systems.     

A fuzzy-based approach for strategic choices in electric energy supply. The case of a Swiss power provider on the eve of electricity market opening

Risk evaluation and strategic choice has become very complex for power providers, because of the growing number of uncertain parameters involved, such as energy market prices, water inflow, and demand. The lack of information and the absence of the decision maker's perception are just some of the many elements that must be accounted for. Therefore, with an approach based on fuzzy set theory, this paper aims to propose a methodology based on strategic choices that will enable decision makers to evaluate the performance of their strategies and portfolios through the computation of an indicator of economic performance, for different time-horizons. By subsequently considering the different imprecise parameters—such as the electricity spot price, the natural gas market price, rainfall and snow, etc.—in the assessment of different strategies and the analyzation of their impacts through scenario analysis, it is concluded that the resulting profit depends not only on the perception of the market player, but also on the imprecision of the variables—the same strategy may produce two different results under a different combination of parameters—as well as on the time-horizon considered. On a simple basis, it has also been possible to compare portfolios of customers.