A Personnel Selection Problem in Healthcare System Using Fuzzy-TOPSIS Approach

The methods of multiple criteria decision-making (MCDM) are increasingly becoming the most desired tools for making daily decisions in various fields of human endeavors. Staff employment in any sector requires a thorough evaluation of the applicant before selection to ensure effective and efficient service delivery. Besides, healthcare is one of the most complicated organizations dealing with human lives. This paper has developed a staff selection model considering a fuzzy environment by using the technique for order preference similar to the ideal solution (TOPSIS) method. For the delivery and promotion of quality healthcare systems, medical staff selection is crucial to the system. Therefore, the study evaluates medical staff by using the expert''s linguistic judgement under the criteria of skill, experience and ability to respond to a problem. The expert''s vagueness in judgments has been represented by using fuzzy triangular numbers. The study determines the closeness coefficient, the measures of separation and the ideal solutions of the TOPSIS method. The most appropriate medical staff are ranked and selected based on the available criteria. The Fuzzy-TOPSIS method is simple and can help other organizations achieve proper ranking, evaluation and selection of qualified candidates, as it takes imprecise information into account.     

航空公司部分多属的枢纽机场定价研究

平台经济理论的运用是机场管理研究的新视角.以机场为平台商,航空公司和乘客为平台用户,在平台经济的分析框架下,以Armstrong价格模型为基础,并吸收Hotelling模型关于平台竞争及客户异质性的构建思想,针对竞争性的枢纽机场的定价策略进行研究.结果表明:机场的定价策略与航空公司和乘客的网络外部性参数和需求的价格弹性、乘客的预期交易次数、机场服务成本有关;倾斜的定价策略和航空收入与非航空收入的交叉补贴并不适用于模型假设下的机场.     

Using decision rules to achieve mass customization of airline services

This paper uses the Dominance-based Rough Set Approach (DRSA) to formulate airline service strategies by generating decision rules that model passenger preference for airline service quality. DRSA could help airlines eliminate some services associated with dispensable attributes without affecting passenger perception of service quality. DRSA could also help airlines achieve mass customization of airline services and generate additional revenues by active or passive targeting of quality services to passengers.     

IBM journey management library: an arena system for airport simulations

Airline passenger terminal congestion caused by increasing passenger traffic results in unsatisfactory levels of customer service. We discuss a simulation modelling tool to help airlines and airports to use advanced technology to improve service to passengers. The tool consists of custom designed, reusable modules that represent the most common airline and airport system data, logic and processes. A model of an actual airline operation based on this approach is described.     

服务管理目标优化配置的Fuzzy-QFD线性规划模型构建与求解

由于服务管理的复杂性和模糊性,现有方法难以有效解决基于主观语言评价的服务质量改进问题。本文拓展了质量功能展开(QFD)方法在服务业中的应用,通过构建一个模糊线性规划模型,以求解最大化提高顾客需求综合满意度的企业能力优化配置问题。首先基于顾客感知-期望差距的模糊评估确定顾客需求、需求权重和边界约束等模型参数,接着运用模糊线性回归和非对称三角模糊数的隶属函数,将含有模糊变量的模糊线性规划问题转化为经典线性规划问题,进而求得不同模糊条件下的模型解。最后通过网购平台的实例验证了模型的有效性和可行性。     

基于模糊综合评价的商务网站质量诊断

高质量网站是企业成功开展电子商务的关键,如何确定影响网站质量的主要因素常常困扰着技术维护人员.鉴于商务网站的复杂性和质量评价的模糊性特点,提出了基于多属性多层次模糊综合评价模型的质量诊断方法,通过对国内某著名商务网站进行质量诊断的算例详细说明了诊断的步骤并验证了该方法的有效性,并讨论了质量评价和诊断系统实施和进一步提高评价结果客观性的方法.     

基于改进的多层次模糊综合评价模型的高校课堂教学质量评价研究

依据模糊数学的理论,构造了一种改进的多层次模糊综合评价模型.通过建立高校课堂教学质量评估指标体系,利用改进的多层次模糊综合评价模型对高校课堂教学质量进行综合评价.实证结果表明,模型具有较好的科学性和实用性,是一种有效地评估高校课堂教学质量的方法.     

Selecting optimum maintenance strategy by fuzzy interactive linear assignment method

In the current competitive environment managers of manufacturing and service organizations try to make their organizations competitive by providing timely delivery of high quality products. Maintenance, as a system, plays a key role in reducing cost, minimizing equipment downtime, improving quality, increasing productivity and providing reliable equipment and as a result achieving organizational goals and objectives. This paper presents a new approach for selecting optimum maintenance strategy using qualitative and quantitative data through interaction with the maintenance experts. This approach has been based on linear assignment method (LAM) with some modifications to develop interactive fuzzy linear assignment method (IFLAM).     

Salespeople's management of customer information: Impact on optimal territory and sales force sizes

Collecting and processing territory and account information are major aspects of a salesperson's task. To a large extent, salespeople's effectiveness depends on the amount and quality of the market information available to them (such as their customers' needs and potential, the likelihood of getting an order after some contact time, etc.). Although they are not always easy to disentangle, these information gathering and processing activities on one hand, and the effective contact time devoted to selling to clients and prospects on the other, vie for the limited time resources available to a salesperson. This paper provides a simple statistical procedure for estimating the costs of information gathering and processing by a salesperson. The model can be used by management for estimating the most profitable territory size to be assigned to each salesperson, and consequently for estimating the optimal sales force size.     

A fuzzy goal programming approach for mid-term assortment planning in supermarkets

We develop a fuzzy mixed integer non-linear goal programming model for the mid-term assortment planning of supermarkets in which three conflicting objectives namely profitability, customer service, and space utilization are incorporated. The items and brands in a supermarket compete to obtain more space and better shelf level. This model offers different service levels to loyal and disloyal customers, applies joint replenishment policy, and accounts for the holding time limitation of perishable items. We propose a fuzzy approach due to the imprecise nature of the goals’ target levels and priorities as well as critical data. A heuristic method inspiring by the problem-specific rules is developed to solve this complex model approximately within a reasonable time. Finally, the proposed approach is validated through several numerical examples and results are reported.     

基于联系数的预评模型在高铁客运站服务质量评价中的应用

高铁客运站服务质量评价是挖掘铁路运输服务中的薄弱环节的重要手段之一.针对现有评价系统的不完备性,将基于联系数的预评模型应用于高铁客运站服务质量评价中.模型通过计算评价系统的联系数,进一步计算出评价特征值来对高铁客运站服务质量进行评价,并利用集对势对服务质量的发展趋势作定性预测.将此方法应用于广州铁路集团衡阳东高铁站中,结果表明,模型具有较好的可操作性与可靠性,并兼顾评价与预测的功能,为高铁客运站服务质量评价工作的开展提供了一种新的理论方法.     

The maximum capture problem with random utilities: Problem formulation and algorithms

A model for the optimal location of new facilities in a competitive market is introduced under the hypothesis that customers' behavior can be modeled by random utility functions. It means that the company, that wished to locate, uses a random utility model to forecast the market share of a location. Therefore the company cannot forecast the behavior of every customer in a deterministic fashion, but is able to embed him by a probability distribution. Three formulations are proposed to compute upper bounds of the objective function and compared in a numerical simulation. A branch and bound method is developed and tested on examples with up to 50 potential locations, and a Variable Neighborhood Search heuristic is proposed to solve larger instances.     

A possibilistic decision model for new product supply chain design

This paper models supply chain (SC) uncertainties by fuzzy sets and develops a possibilistic SC configuration model for new products with unreliable or unavailable SC statistical data. The supply chain is modeled as a network of stages. Each stage may have one or more options characterized by the cost and lead-time required to fulfill required functions and may hold safety stock to prevent an inventory shortage. The objective is to determine the option and inventory policy for each stage to minimize the total SC cost and maximize the possibility of fulfilling the target service level. A fuzzy SC model is developed to evaluate the performance of the entire SC and a genetic algorithm approach is applied to determine near-optimal solutions. The results obtained show that the proposed approach allows decision makers to perform trade-off analysis among customer service levels, product cost, and inventory investment depending on their risk attitude. It also provides an alternative tool to evaluate and improve SC configuration decisions in an uncertain SC environment.     

Network Design for Express Shipment Delivery

Service network design problems arise at airlines (passenger and cargo), trucking companies, railroads, etc., wherever there is a need to determine cost minimizing routes and schedules, given constraints on resource availability and level of service. We focus on a particular service network design application, namely, the express shipment delivery problem, and we develop models and a solution technique designed specifically for large-scale express delivery problems with time windows. Using data from an express delivery company, we demonstrate that our approach can produce savings in total operating costs and provide a valuable tool for making decisions at strategic and tactical levels.     

Preference disaggregation for measuring and analysing customer satisfaction: The MUSA method

The MUlticriteria Satisfaction Analysis (MUSA) method for measuring and analysing customer satisfaction is presented in this paper. The MUSA method is a preference disaggregation model following the principles of ordinal regression analysis (inference procedure). The integrated methodology evaluates the satisfaction level of a set of individuals (customers, employees, etc.) based on their values and expressed preferences. Using satisfaction survey's data, the MUSA method aggregates the different preferences in unique satisfaction functions. This aggregation–disaggregation process is achieved with the minimum possible errors. The main advantage of the MUSA method is that it fully considers the qualitative form of customers' judgements and preferences. The development of a set of quantitative indices and perceptual maps makes possible the provision of an effective support for the satisfaction evaluation problem. This paper also presents the reliability analysis of the provided results, along with a simple numerical example that demonstrates the implementation process of the MUSA method. Finally, several extensions and future research in the context of the presented method are discussed.     

Threshold policies for controlled retrial queues with heterogeneous servers

Retrial queues are an important stochastic model for many telecommunication systems. In order to construct competitive networks it is necessary to investigate ways for optimal control. This paper considers K -server retrial systems with arrivals governed by Neut' Markovian arrival process, and heterogeneous service time distributions of general phase-type. We show that the optimal policy which minimizes the number of customers in the system is of a threshold type with threshold levels depending on the states of the arrival and service processes. An algorithm for the numerical evaluation of an optimal control is proposed on the basis of Howar's iteration algorithm. Finally, some numerical results will be given in order to illustrate the system dynamics. AMS subject classification: 60K25 93E20     

A fuzzy logic-based decision model to satisfy goals for successful product/service introduction

The Dempster–Shafer theory of evidence is applied to a multiattribute decision-making problem where the decision maker must determine which of several products/services have the best opportunity for success in a competitive marketplace. Multiattribute decisions are generally constrained by the uncertainty inherent in assessing the relative importance of each attribute element that is needed for success and the evaluation of the product/service to be introduced. The relative importance of each attribute element deemed necessary for success is assessed by the decision maker as a goal to be met. The evaluation of each product/service is addressed through expert opinion about the degree to which each element is contained in each product/service. Then the belief and plausibility that a product/service will satisfy the decision maker's goal are calculated. The decision to introduce a product or service depends on the evaluation of the anticipated loss from introduction of a product/service into a competitive market.     

面向电子商务服务水平的变权分析评价方法

针对电子商务服务水平评价问题,提出一种基于变权分析方法的评价方法。首先,建立电子商务服务水平评价指标体系;其次,采用实数、区间数、三角模糊数、语言变量和直觉模糊数5种不同类型表示其评价信息,提出各个电子商务服务水平关于正理想解的相对满意度计算方法,据此确定电子商务服务水平,并具体给出其变权分析评价步骤;最后,通过实例说明该方法的有效性和合理性。     

Network structure,perception level,and participants' welfares

Based on a market consisting of one monopoly and several customers who are embedded in an economic network, we study how the different perception levels about the network structure affect the two kinds of participants' welfares, and then provide some good strategies for the monopoly to mine the information of the network structure. The above question is the embodiment of the “complex structure and its corresponding functions” question often mentioned in the field of complexity science. We apply a two‐stage game to solve for the optimal pricing and consumption at different perception levels of the monopoly and further utilize simulation analysis to explore the influence patterns. We also discuss how this theoretic model can be applied to a real world problem by introducing the statistical exponential random graph model and its estimation method. Further, the main findings have specific policy implications on uncovering network information and demonstrate that it is possible for the policy‐maker to design some win–win mechanisms for uplifting both the monopoly's profit and the whole customers' welfare at the same time. © 2014 Wiley Periodicals, Inc. Complexity 21: 349–362, 2015     

Fuzzy pricing,marketing and service planning in a fuzzy inventory model: A geometric programming approach

In the real world markets, demand is influenced by different parameters. Recently, many researchers have been interested in integrated production and marketing planning strategies in inventory models where demand depends on different parameters such as price and/or marketing expenditure. The quality of services that are offered to customers of a product is one of the most important parameters that affects demand in the real markets and has not been considered in development of inventory models. On the other hand, the cost parameters in real inventory systems and other parameters such as price, marketing and service elasticity to demand are imprecise and uncertain in nature. So, the notion of fuzziness can be applied to cope with this uncertainty. In this paper, a new fuzzy profit maximization inventory model with shortages is proposed. The demand is considered as a power function of price, marketing expenditure and service expenditure. Furthermore, unit cost is determined as a power function of order quantity. Since the proposed model is in a fuzzy environment, a fuzzy decision should be made to meet the decision criteria, and the results should be fuzzy. Therefore, the proposed model is formulated and solved using geometric programming and fuzzy optimization techniques to derive an approximation of the results’ membership functions. The model is illustrated with a numerical example and finally a case study is provided for evaluation and validation of the results of model.