Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

Staff rostering in call centers providing employee transportation

We address the staff rostering problem in call centers with the goal of balancing operational cost, agent satisfaction and customer service objectives. In metropolitan cities such as Istanbul and Mumbai, call centers provide the transportation of their staff so that shuttle costs constitute a significant part of the operational costs. We develop a mixed integer programming model that incorporates the shuttle requirements at the beginning and end of the shifts into the agent-shift assignment decisions, while considering the skill sets of the agents, and other constraints due to workforce regulations and agent preferences. We analyze model solutions for a banking call center under various management priorities to understand the interactions among the conflicting objectives. We show that considering transportation costs as well as agent preferences in agent-shift assignments provides significant benefits in terms of both cost savings and employee satisfaction.     

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

We used an agent‐based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision‐making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers’ behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system‐level responses are predicted using a bottom‐up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food‐safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.     

Quality self-control and co-supervision mechanism of construction agent in public investment project in China

Public investment project (PIP) plays an important role in the China economy. In order to improve the project management performance of public projects, the government is searching for a scientific system to build a construction management supervision mode. This paper introduces the policy background and connotation of Agent Construction System (ACS). As a public investment construction management model, ACS, is gradually being incorporated into the legal framework, it is necessary to improve the construction agent supervision mechanism. This article analyzes the supervision mechanism of construction agent quality management under the principle of two-stage agent mode and establishes an agent quality self-control system and a government co-supervision system. These systems take the contract management as the core and the project quality objective as the guidance. These systems also consist of a two-dimensional framework of vertical self-control and horizontal supervision, which form a quality supervision mechanism. Based on Rough Set theory, the article proposes the idea of building an agent quality self-control and government co-supervision model, and illustrates it with a flow chart for building the model, which paves the way of quantitative research for the future.     

基于智能Agent技术的个性化数字图书馆系统模型

根据智能Agent的特性将其应用于智能信息检索,并应用于图书管理系统。针对个性化数字图书馆的具体需求,对原图书馆系统进行了功能扩充。     

基于Multi—Agent的供应链企业逆向物流库存模型研究

为了更好更快地实现国家规定的循环经济目标，当今企业也积极参与建设逆向物流工程。库存问题是逆向物流研究中最重要的内容之一，在采用Agent的建模思想基础上，充分考虑影响逆向物流供应链库存管理的各种复杂因素，抽象出交互、制造商、销售商、回收、信息和设计商等六大供应链逆向物流功能，由此组成供应链逆向物流库存系统的六类Agent，从而建立了基于Multi—Agent的逆向物流供应链库存控制模型。     

基于Agent的数字图书馆个性化信息推送服务模型研究

在通过对Agent技术含义与特性分析的基础上,本文探讨了个性化信息推送服务的形式以及在Agent技术下的各种个性化信息推送服务的模式,详细分析了基于Agent技术的个性化信息推送服务的工作原理。     

基于多Agent的物流协作联盟组建研究

物流协作联盟能够有效的整合物流服务资源，提高物流服务商的运作效率，同时能够适应物流服务商分布自治、动态变化的特征。本文以多Agent构建的物流协作系统为基础，利用协商机制和粒子群算法来研究物流协作联盟的组建。该联盟的组建能够很好的满足个体利益需求，同时又保证联盟的整体收益。     

医药行业:从暴利走向均衡——药品代理经销商的未来地位与对策研究

本文认为随着药品降价风起 ,医药行业中代理经销商的有利地位正在受到动摇 ,必须本着代理产品横向多样化、纵向梯队化的原则实施全新的市场竞争策略 ,同时 ,努力发展成为药品物流中心是今后代理营销商的新角色     

论电子商务中的个性化信息服务

本文简要介绍了个性化信息服务的概念以及电子商务中个性化信息服务的意义,分析了电子商务中个性化信息服务的类型,并结合Agent技术、RSS技术以及Web挖掘技术,详细探讨了电子商务个性化信息服务的实现.