两机器越库调度问题的模拟退火算法

研究两机器越库流水作业调度问题,其目标函数是最小化加权完工时间。首先,对算法参数进行分析,并针对所研究问题的特点对参数选取进行试验分析;其次,基于参数选取的数值分析结果,给出求解该问题的模拟退火算法;最后,通过数值实验进一步表明该算法的有效性。     

Personalized multi-period tour recommendations

During a trip planning, tourists gather information from different sources, select and rank the places to visit according to their personal interests, and try to devise daily tours among them. This paper addresses the complex selection and touring problem and proposes a “filter-first, tour-second” framework for generating personalized tour recommendations for tourists based on information from social media and other online data sources. Collaborative filtering is applied to identify a subset of optional points of interest that maximize the potential satisfaction, while there are some preselected mandatory points that the tourists must visit. Next, the underlying orienteering problem is solved via an Iterated Tabu Search algorithm. The goal is to generate tours that contain all mandatory points and maximize the total score collected from the optional points visited daily, taking into account different day availabilities and opening hours, limitations on the tour lengths, budgets and other restrictions. Computational experiments on benchmark datasets indicate that the proposed touring algorithm is very competitive. Furthermore, the proposed framework has been evaluated on data collected from Foursquare. The results show the practical utility and the temporal efficacy of the recommended tours.     

Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data

We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting.     

How collaborative routines improve dynamic innovation capability and performance in tourism industry? A path-dependent learning model

Current results of direct relationships between collaboration and innovation capability on performance in tourism contexts are inconsistent. This research is to uncover roles of collaborative routines on promoting relationships between internal and service innovation capabilities as two distinct mechanisms, and performance. The study also examines the contingent effect of knowledge search on performance. Survey data from 181 samples from the Thai tourism industry are gathered for analyses. Findings demonstrate that knowledge search and internal innovation capability have a direct impact on performance, whereas the effect of service innovation capability on performance is significant only in the presence of collaborative routines.     

Web-based GIS in tourism information search: Perceptions,tasks, and trip attributes

People’s strategies and choices to utilize tourism information have shifted dramatically over the years following ubiquitous access to the Internet. Despite the fact that many tourism information searches on the Internet involve geo-spatial information through WebGIS, little is known about tourists’ behavioral patterns with this media. The purpose of this study was to examine tourists’ trip situations, tasks, and perceptions toward WebGIS. An electronic survey method and multiple regression technique were used to collect and analyze data. Findings indicate that ‘usefulness’ and ‘playfulness’ were the key factors that determined the level of usage and interaction. Users showed distinct behavioral tendencies under different trip situations and task performances when searching tourism information using WebGIS.     

Web users’ behavioural patterns of tourism information search: From online to offline

This paper presents a conceptual framework of Web users’ engagement in tourism information search for a comprehensive understanding of their integrated online and offline search behaviour. The information search experiences are characterised as a process constituting some common elements: prior knowledge and searching experiences, online searching strategies, processing and recording information, barriers to online searching, reasons for ending an online search, summarising information, exchanging information and searching for more information through other sources. Such behaviour goes beyond the scope of information searching and captures the other activities, including information processing, utilising and disseminating. The grounded theory research method is employed as an inductive investigative process in which the authors construct the framework by systematically collecting and analysing data. The aim of this research method is to build a theory. The data sets consist of both semi-structured in-depth interviews with subjects and their field observations based on online searching. A theoretical model incorporating 10 propositions is proposed for future testing.     

Expert systems and land development expertise

Summary

Expert systems are a product of the new technology. They provide the means for computerizing human expertise. This necessitates a more explicit understanding of the latter, provides an additional source of it and presents the possibility of enhancing the competence of that expertise. The paper argues that in the face of increased competition for investment funds the development industry needs to adopt a more sophisticated approach to project assessment. Two examples, with respect to planning law and retail investment appraisal, are developed to indicate the potential of the expert system approach. Ultimately expert systems challenge appeals to ‘feel’, ‘experience’ and judgement’ in human decision‐making; if successful, however, they promise improved profitability.     

物联网环境下基于智能代理的建材交易平台研究

通过物联网环境下的基于智能代理的建材交易平台,建立起“人”与“物”之间的应用,将各建材企业的自动化立体仓库作为物流基础设施,利用自动化立体仓库的数据库系统构建Web站点,为建材交易平台提供基础数据支持,并以比较搜索引擎为核心,通过各智能代理模块的交互实现该平台的各项功能.     

Neighborhood quality and labor market outcomes: Evidence from quasi-random neighborhood assignment of immigrants

Settlement in a socially deprived neighborhood may hamper individual labor market outcomes because of lack of employed or highly skilled contacts. I investigate this hypothesis by exploiting a unique natural experiment that occurred between 1986 and 1998 when refugee immigrants to Denmark were assigned to municipalities quasi-randomly, which successfully addresses the methodological problem of endogenous neighborhood selection. I show that individuals sort into neighborhoods. Taking account of location sorting, living in a socially deprived neighborhood does not affect labor market outcomes of refugee men. Their labor market outcomes are also not affected by the overall employment rate and the overall average skill level in the neighborhood. However, an increase in the average skill level of non-Western immigrant men living in the neighborhood raises their employment probability, while an increase in the employment rate of co-national men living in the neighborhood raises their real annual earnings. This provides quasi-experimental evidence that residence-based job information networks are ethnically stratified.     

轻量级工作流引擎LShark的研究与开发

文章基于关系数据库建模,构造一个轻量级的工作流引擎LShark。设计的主体是模型库与运行库,使数据库服务器和工作流引擎融为一体,既降低了开发工作流引擎的难度,又使其能和应用系统无缝连接,能够为在不同平台上开发工作流管理系统提供支持。