“凤凰古城”旅游目的地品牌营销研究

旅游目的地营销已进入品牌竞争时代,品牌作为引导旅游者识别和辨认旅游目的地产品和服务特征以及让旅游者对旅游目的地原本无形的旅游经历产生一种体验式的憧憬和向往的重要途径,正逐步受到各旅游目的地的关注。在分析＂凤凰古城＂旅游目的地品牌现状基础之上,构建了＂凤凰古城＂旅游目的地品牌＂重塑—传播—管理＂的整体性营销策略体系,期望对于提升＂凤凰古城＂旅游目的地品牌竞争力、增强其可持续发展能力提供些许借鉴。     

运输路径问题的一个新启发式算法

在解运输路径问题时常常使用Clarke和Wright提出的启发式算法(下称C.W.算法)。本文对Clarke和Wright算法进行改进。改进算法的计算复杂性虽不如C.W.算法,但计算的数值结果在大多数情况下比C.W.算法的结果更好。     

梁园之游：文人群体创作活动的始足之旅

梁园之游是中国文学史上一件值得注意的盛事。它虽然出现在文学尚未独立于经史的西汉初年,但它实际上已经具备了文人群体创作活动的基本特征,可以说是中国古代文人群体创作活动的始足之旅。梁园之游对后来出现的文人群体创作活动产生了深远影响。建安时期的邺下之游,正始名士的竹林之游,西晋石崇等人的金谷园之游,以及后世文人的群体创作活动,都或多或少地带有梁园之游的某些特征。     

The Clustering of Categorical Data: A Comparison of a Model-based and a Distance-based Approach

For clustering multivariate categorical data, a latent class model-based approach (LCC) with local independence is compared with a distance-based approach, namely partitioning around medoids (PAM). A comprehensive simulation study was evaluated by both a model-based as well as a distance-based criterion. LCC was better according to the model-based criterion and PAM was sometimes better according to the distance-based criterion. However, LCC had an overall good and sometimes better distance-based performance as PAM, although this was not the case in a real data set on tribal art items.     

Strategic Purchases of Bundled Products in a Health Care Supply Chain Environment*

Recent articles in the Wall Street Journal summarize the state of business practice in American hospitals by shedding light on the state of supply chain management practices and foci in today's health care supply chains. In health care, the single largest cost after labor is materials, and it has been documented that health care facilities can reduce the environmental impacts of the products and services they consume before regulatory problems arise or waste disposal costs increase by focusing on their upstream activities. Health care systems around the country consume significant quantities and varieties of products within the health delivery processes. Solving these environmental problems requires a much broader view involving collaborative efforts of professionals from different areas of health care to meet these challenges. The purchasing function bridges the gaps by providing a healthy dialogue on key environmental attributes within the health care supply chain. The concept of bundling new with refurbished products is gaining a lot of attention in the health care supply chain. This research describes a health care purchasing problem for bundling new and refurbished products of the type facing a growing number of large health care providers, and then proposes a methodology for evaluating the complex tradeoffs involved in bundling decisions for refurbished health care products. By exploiting some useful properties of the problem structure, our results provide buyers with useful insights for examining and selecting suppliers who are willing to offer bundles of new and refurbished products.     

The bandpass problem: combinatorial optimization and library of problems

A combinatorial optimization problem, called the Bandpass Problem, is introduced. Given a rectangular matrix A of binary elements {0,1} and a positive integer B called the Bandpass Number, a set of B consecutive non-zero elements in any column is called a Bandpass. No two bandpasses in the same column can have common rows. The Bandpass problem consists of finding an optimal permutation of rows of the matrix, which produces the maximum total number of bandpasses having the same given bandpass number in all columns. This combinatorial problem arises in considering the optimal packing of information flows on different wavelengths into groups to obtain the highest available cost reduction in design and operating the optical communication networks using wavelength division multiplexing technology. Integer programming models of two versions of the bandpass problems are developed. For a matrix A with three or more columns the Bandpass problem is proved to be NP-hard. For matrices with two or one column a polynomial algorithm solving the problem to optimality is presented. For the general case fast performing heuristic polynomial algorithms are presented, which provide near optimal solutions, acceptable for applications. High quality of the generated heuristic solutions has been confirmed in the extensive computational experiments. As an NP-hard combinatorial optimization problem with important applications the Bandpass problem offers a challenge for researchers to develop efficient computational solution methods. To encourage the further research a Library of Bandpass Problems has been developed. The Library is open to public and consists of 90 problems of different sizes (numbers of rows, columns and density of non-zero elements of matrix A and bandpass number B), half of them with known optimal solutions and the second half, without.     

基于混合算法的具有硬时间窗口约束的VRPSPD问题

具有硬时间窗口约束下同时收发的车辆路径问题（vehicle routing problem with simultaneous pick-up and delivery with hard time windows,VRPSPD with Hard TW）是将产品配送和废物回收统一进行优化的问题。本文研究了一个中心仓库,多台车辆向具有配送需求和回收需求的客户提供服务,客户存在硬时间窗口要求的车辆运输问题。该问题中,客户的配送需求和回收需求必须同时获得满足,即客户仅允许被访问一次,且需求不可分割,只能由一台车辆提供服务。且客户的硬时间窗口要求必须获得满足。首先将修正后的旅程分割方法应用于硬时间窗口约束下的VRPSPD问题初始解的获得,并利用响应性禁忌搜索算法框架,结合基于多种领域的可变式搜索方法,给出一启发式算法。计算机实验结果表明,该启发式算法在求解VRPSPD with hard TW上是有效的。     

Approaches to a real-world Train Timetabling Problem in a railway node

We consider the Train Timetabling Problem (TTP) in a railway node (i.e. a set of stations in an urban area interconnected by tracks), which calls for determining the best schedule for a given set of trains during a given time horizon, while satisfying several track operational constraints. In particular, we consider the context of a highly congested railway node in which different Train Operators wish to run trains according to timetables that they propose, called ideal timetables. The ideal timetables altogether may be (and usually are) conflicting, i.e. they do not respect one or more of the track operational constraints. The goal is to determine conflict-free timetables that differ as little as possible from the ideal ones.The problem was studied for a research project funded by Rete Ferroviaria Italiana (RFI), the main Italian railway Infrastructure Manager, who also provided us with real-world instances. We present an Integer Linear Programming (ILP) model for the problem, which adapts previous ILP models from the literature to deal with the case of a railway node. The Linear Programming (LP) relaxation of the model is used to derive a dual bound. In addition, we propose an iterative heuristic algorithm that is able to obtain good solutions to real-world instances with up to 1500 trains in short computing times. The proposed algorithm is also used to evaluate the capacity saturation of the railway nodes.     

选址-分配问题的一个算法

本文就常见的所谓选址一分配问题,在提出了一个较为简单的多项式算法。在采种条件下,所得到的解是最优解,文中所提出的模型不局限于配电系统,亦可适应其它各种类似的集散系统。文末给出了一个计算实例。     

What are you calling intuitive? Subject heterogeneity as a driver of response times in an impunity game

Studies on the intuitive or deliberate nature of human actions often use time constraints for identification, assuming that constrained individuals fall back to intuitive behavior. This identification strategy disregards individual heterogeneity and self-priming, i.e. the behavioral rule that subjects can form during the instructions phase, and then apply irrespective of the time constraint. We use respondent data from an impunity game as an example of how subject heterogeneity can drive results. 24 respondents face 240 more or less unfair allocation proposals out of a small or large pie and can accept or reject the offer. Upon rejection respondents burn their own money, but not the proposer’s. Respondents decisions are communicated to the proposer. On average, emotional rejections take longer than deliberate acceptances. Including individual heterogeneity, though, we find that subjects who mostly accept (reject) take more time to reject (accept). Faster decisions are the ones conforming with the modal early reaction. We attribute this finding to heterogeneity in self-priming. Since self-priming is orthogonal to time constraints, it has the capacity to invalidate their use in the identification of dual decision modes.