A Consensus Based Method for Multi-criteria Group Decision Making Under Uncertain Linguistic Setting

A two-stage (a consensus process and a selection process) approach is proposed to solve multi-criteria group decision making problems under an uncertain linguistic environment. Since achieving general consensus is a desirable goal in group decision making, the proposed method first develops a consensus reaching process in order to reach a satisfactory consensus. Based on the partial order of uncertain linguistic variables, the superiority index of one alternative over another for a given criterion and the overall superiority index of one alternative are defined. Then a procedure based on the superiority indices is described to select the best alternative(s). Given the decision makers’ desire for a consensus solution, a common framework based on the previous consensus model and the selection process is presented. Finally, a practical application is demonstrated to show the effectiveness of the proposed method.     

A Fuzzy Stochastic Multi-Attribute Group Decision-Making Approach for Selection Problems

The purpose of this paper is to demonstrate how the fuzzy and stochastic approaches as well as multi-attribute group decision-making techniques can be effectively utilized for selection problems in different kinds of uncertainty situations. A group of the decision makers describes a value for an alternative with respect to an attribute by the use of linguistic variables. The rating of each alternative is aggregated, which can be expressed as triangular fuzzy numbers. Then Monte Carlo simulation is applied to generate the performance distribution of alternatives with respect to different attributes in an uncertain environment. Finally, a stochastic compromise ranking technique, known as the VIKOR technique, is developed to evaluate probability distributions for each alternative on each attribute and to prioritize them. The proposed fuzzy stochastic approach is suitable to compromise a solution among the conflicting tangible and intangible attributes under the group decision-making process. In addition, an application of the proposed approach is provided to solve the important risk selection problem in a highway project. The results illustrate its real-life applicability and suitability in discrete group decision-making under uncertainty.     

Non-numeric multi-criteria multi-person decision making

We describe a decision making technique, ME-MCDM, for the evaluation and selection of alternatives using a non-numeric scale. Using this procedure each alternative is evaluated by an expert for satisfaction to a multi-criteria selection function. Each criterion can have a different degree of importance. The individual expert evaluations can then be aggregated to obtain an overall evaluation function. We apply this technique to the problem of proposal selection in the funding environment. In this environment the technique is augmented by some textual information which can also be used to help in the decision process.     

Dynamic internet pricing with service level agreements for multihomed clients

With the increase in internet coverage and the decrease in internet access price, the demand for good internet service has grown. Clients expect a guarantee in the quality of service (QoS) during internet access. In this paper, we present a model in which clients are given assurances by service providers to be able to connect to the internet and to get the bandwidth requested, and, if clients do not get the services they request, the service provider pays penalties to the clients. We consider internet clients that can dynamically connect to a number of internet service providers (ISP). When a client arrives at an ISP, he has to decide whether to accept the client, and then the price to charge from the client for the duration of its connection. Rejection of a client results in a penalty and delay in getting the requested bandwidth also incurs a penalty. We assume a Poisson arrival process with the rate of arrival sensitive to the price being charged. A client requests bandwidth for a time that is exponentially distributed, then the client is idle for a time that is also exponentially distributed; and then either the client departs or requests bandwidth again after the idle period is over. A service provider tries to maximize its income by charging appropriate prices based on its current state and deciding whether to accept more clients or not. Since penalties are imposed, such solutions also automatically balance load among service providers, and so the QoS to clients improves. We present solutions that maximize the income of service providers. The solutions are then compared using simulation. Simulation results show that our solutions significantly improve QoS of clients and increase the income of service providers as compared to a simple heuristic based solution that could otherwise be used.     

A Study of Factors Influencing Parental Patronage of Quick Service Restaurants

Summary

This study identified factors influencing parental quick service restaurant patronage. Results indicated that parents are influenced to patronize quick service restaurants most often by speed of service, menus that offered their childrens' favorite food items, and parents' lack of time for meal preparation at home. Children preferred French fries, pizza, hamburgers, cheeseburgers, and chicken nuggets at quick service restaurants. French fries, the favorite childrens' fast food menu selection, was ranked by respondents as one of the least healthy food items, while mashed potatoes, one of childrens' least favorite fast food menu selections, was perceived to be one of the healthier food selections by parents. Restaurateurs were encouraged to develop newer, healthier methods of preparing these popular menu items while offering more nutritious menu selections for children.     

A Study on Aggregation of TOPSIS Ideal Solutions for Group Decision-Making

The technique for order preference by similarity to ideal solution (TOPSIS) has become a popular multi-criteria decision making (MCDM) technique, since it has a comprehensible theoretical structure and is able to provide an exact model for decision making. For the use of TOPSIS in group decisions, the common approaches in aggregating individual decision makers’ judgments are the geometric and the arithmetic mean methods, although these are too intuitive and do not consider either preference levels or preference priorities among alternatives for individual decision makers. In this paper, a TOPSIS group decision aggregation model is proposed in which the construction consists of three stages: (1) The weight differences are calculated first as the degrees of preferences among different alternatives for each decision maker; (2) The alternative priorities are then derived, and the highest one can be denoted as the degree to which a decision maker wants his most favorite alternative to be chosen; (3) The group ideal solutions approach in TOPSIS is used for the aggregation of similarities obtained from different decision makers. A comparative analysis is performed, and the proposed aggregation model seems to be more satisfactory than the traditional aggregation model for solving compromise-oriented decision problems.     

Effects of pricing on Internet user behavior

The INternet Demand EXperiment (INDEX) conducts experiments to measure demand for quality-differentiated Internet access as a function of bandwidth, traffic volume, applications, and pricing structure. This paper presents an overview of results based on aggregated data from five pricing experiments. In these experiments, pricing is based either on time, volume, a combination of both, or a flat-rate buy out option. Quality of Service (QoS) is differentiated by varying bandwidth for incoming and outgoing traffic. After describing the experimental design and characterizing our subject pool using demographic data, we examine the change in service usage by comparing the five experiments in terms of traffic generation, QoS selection, and expenditure.     

Multi-criteria Remote Asynchronous Group Decision Screening: An Experimental Study

A new visualization-based multi-criteria procedure for group decision screening is presented. The procedure supports a group in selecting a small number of alternatives from an initial list described by a collection of attributes which are used as screening criteria. We propose and experimentally study the Group Remote Asynchronous Screening Support (GRASS) procedure that can be used by a large number of participants who are not able to meet face to face. GRASS does not use any interaction between the participants and the group screening is based on the individual preferences expressed by them independently from each other. GRASS uses the concepts of Borda count, by applying the visualization of information to simplify the analysis of large lists of multi-criteria alternatives. Visualization is used to support the individual analysis of the variety of alternatives and the individual selecting of a small number of alternatives from the list for the subsequent scoring through Borda count. Visualization is carried via the Interactive Decision Maps / Reasonable Goals Method (IDM/RGM) technique. We first check a speculative supposition that participants are able to find a single best alternative by using the GRASS procedure. As it is not the case, we re-formulate our hypothesis and check whether the most preferred alternative is part of a short list of alternatives returned through GRASS. The experiment was carried out with senior applied mathematics students who managed to apply GRASS without any problem.     

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.     

An Extended PROMETHE II Multi-Criteria Group Decision Making Technique Based on Intuitionistic Fuzzy Logic for Sustainable Energy Planning

The implementations of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) category to complex multi-criteria group decision making (MCGDM) scenarios have been included in thousands areas. Outranking methods such as PROMETHEE II are also greatly employed in energy planning application. In MCGDM methods if decision makers (DMs) are not able to treat precise data in order to define their preferences, the intuitionistic fuzzy set (IFS) theory enables them. IFS attributes are connected with the degree of membership and non-membership, and can be used to draw uncertainty in group decision-making situations. In this paper, a new version of the PROMETHEE II method is proposed, aiming at solving MCGDM problems. Linguistic variables are expressed in the membership function and non-membership function of IFS which are used to assess the weights of all criteria and the ratings of each alternative with respect to each criteria. Conditional normalized Euclidean distance measure is adopted to measure deviations between alternatives on intuitionistic fuzzy set. Then, a ranking algorithm is applied to indicate the order of superiority of alternatives. Finally, a practical example is given to an application of sustainable energy planning to verify our proposed method. Additionally, a comparative analysis is done among the proposed PROMETHEE II method and the intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method and elimination and choice translating reality method (IF-ELECTRE).     

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.     

Interval-Valued Intuitionistic Fuzzy WASPAS Method: Application in Reservoir Flood Control Management Policy

Interval-valued intuitionistic fuzzy sets (IVIFSs) are very flexible tool to cope with the uncertainty arises in multi-criteria decision making (MCDM) problems. In recent times, MCDM problems with interval-valued intuitionistic fuzzy information have achieved more attention from researchers in different areas and consequently, several MCDM methods have been extended for IVIFSs. In this paper, a novel approach based on WASPAS method is developed under IVIFSs. The developed method is based on the operators of IVIFSs, some amendments in the classical WASPAS method and a new process for calculation of criteria and decision experts’ weights. In process for calculating weights, new procedures is propoesd to compute the decision experts’ weights and criteria weights based on interval-valued intuitionistic fuzzy information measures (entropy, divergence and similarity measures) to achieve more realistic weights. Innovative information measures are developed based on the exponential function for IVIFSs to determine the weights of the criteria and decision experts. Since the uncertainty is an unavoidable feature of MCDM problems, the developed method can be a constructive tool for decision-making in an uncertain environment. Further, an uncertain decision making problem of reservoir flood control management policy is implemented with interval-valued intuitionistic fuzzy information, which reveals the effectiveness and reliability of the proposed IVIF-WASPAS method. To validate the result, comparative analysis with existing methods and sensitivity analysis are presented under interval-valued intuitionistic fuzzy environment.     

基于Heston's SV模型下带有违约风险的最优再保险-投资策略

对于模糊厌恶型保险公司，在可违约金融市场中，考虑其比例再保险-投资问题。假设在任意时刻保险公司可购买比例再保险和投资无风险资产、风险资产和可违约债券，其中风险资产价格服从Heston's SV (Heston's Stochastic Volatility) 模型。首先，考虑模型不确定性，采用与参考模型概率测度等价的概率测度描述替代模型。利用Girsanov变换得到保险公司在替代模型下的财富过程，并通过动态规划原理建立了相应的HJB (Hamilton-Jacob-Bellman) 方程，其中，文章用含状态依赖的不同偏好参数度量模型不确定性的模糊度。其次，分别在违约前和违约后的情况下，针对CARA (Constant Absolute Risk Aversion) 效用函数求解HJB方程，得到了最优稳键的再保险-投资策略，并给出了数值模拟和经济学解释。结果表明：相比较使用同一偏好参数的模型结果，文章的最优策略的表达式更精确，考虑的模型更符合实际金融环境。     

Creating Media Culture. Snow,Robert P. Beverly Hills: Sage Publications, 1983. 261 pp. $28.00 (h), $14.00 (p)

Abstract

This paper addresses the media selection problem, a special form of resource allocation problem. After reviewing characteristics of media decisions and existing analytical approaches, two approaches incorporating the analytic hierarchy process (AHP) are presented. The recommended approach utilizes AHP in conjunction with integer programming while an alternative approach uses goal programming coupled with the AHP. Those specific characteristics of AHP that make it particularly well suited to the media selection problem are discussed.     

多队列FIFO的设计及其在核心路由器中的应用

提供服务质量保证是目前Internet的重要研究课题之一,而在核心路由器上实现区分的服务质量保证则主要体现在对优先级队列的调度上。文章在分析QDR-SRAM操作时序的基础上,详细介绍了利用FPGA和QDR-SRAM实现多队列FIFO的设计方案,并讨论了通过利用该设计在核心级路由器中实现支持优先级调度的方案。在实际应用中,这种方案的硬件实现简单而且性能良好。     

ROBUST ASSET ALLOCATION WITH BENCHMARKED OBJECTIVES

In this paper, we introduce a new approach for finding robust portfolios when there is model uncertainty. It differs from the usual worst‐case approach in that a (dynamic) portfolio is evaluated not only by its performance when there is an adversarial opponent (“nature”), but also by its performance relative to a stochastic benchmark. The benchmark corresponds to the wealth of a fictitious benchmark investor who invests optimally given knowledge of the model chosen by nature, so in this regard, our objective has the flavor of min–max regret. This relative performance approach has several important properties: (i) optimal portfolios seek to perform well over the entire range of models and not just the worst case, and hence are less pessimistic than those obtained from the usual worst‐case approach; (ii) the dynamic problem reduces to a convex static optimization problem under reasonable choices of the benchmark portfolio for important classes of models including ambiguous jump‐diffusions; and (iii) this static problem is dual to a Bayesian version of a single period asset allocation problem where the prior on the unknown parameters (for the dual problem) correspond to the Lagrange multipliers in this duality relationship. This dual static problem can be interpreted as a less pessimistic alternative to the single period worst‐case Markowitz problem. More generally, this duality suggests that learning and robustness are closely related when benchmarked objectives are used.     

A Negotiation Model for Inducing Higher Service in a Distribution Channel

This paper analyzes, in the context of negotiation, the problem of coordination and conflict resolution between the manufacturer (Seller) and the retailers (Buyers) for a two-tier inventory system. The retailers capture demand (from customers) and therefore are responsible for the level of service offered by the system. The larger the inventory that a retailer has of a particular product, the lower the probability of running out of stock and therefore, avoid the possibility of a lost sale for the manufacturer. A conflict arises (and therefore the negotiation process starts) when the manufacturer wants the retailer to increase the level of service while retailers are satisfied with the status quo. Using the Nash bargaining solution, we develop a theoretical framework that incorporates behavioral dimensions and predicts the outcome of “sharing” the profit. The results indicate the advantage of developing long term relationships among the members of the distribution channel to minimize the uncertainty and therefore the source of conflict.     

A Case Study of Group Decision Method for Environmental Foresight and Water Resources Planning Using a Fuzzy Approach

Group decision-making (i.e., multi-expert) is an important subject in planning water resources. The inherent complexity and uncertainty of real world urge many experts to be involved in decision-making processes. This paper presents an application of the linguistic-label aggregation method in a real-life case study. The case was taken from a foresight exercise in Colombia (South America) concerning environmental and water resources planning in a river basin. The group decision-making problem is solved using a four-step approach based on (i) the evaluation of experts’ opinions, (ii) the aggregation of opinions for each alternative, (iii) fuzzy ranking, and (iv) final assessment. Two main issues that are new in our work is that we consider temporal linguistic labels and a fuzzy ranking procedure that is able to include the mean, the standard deviation, the fuzzy membership function and the frequency of experts’ opinions for each alternative. The approach is developed and implemented on a computational tool. Results show an efficient decision-making process, that is, the tool demonstrated to deal with shortest time frames and to increase the efficiency of the planning resources, mainly because allows the decision manager to focus on the establishment of criteria. The latter also leads to objectivity and eases the identification and discussion of elements of consensus in decisions that otherwise may be embedded in individuals’ interests.     

A Socio-technical Approach for Group Decision Support in Public Strategic Planning: The Pernambuco PPA Case

This article describes a socio-technical approach to public strategic planning. A multi-methodological framework with decision support systems (DSS) of problem structuring, multi-criteria decision analysis and strategic thinking was used in a decision conferencing process to support the key-players of the Pernambuco State Department of Social Development and Human Rights, in Brazil, to elaborate its 2008–2011 Multi-Annual Plan (PPA). This interactive process took place in June 2007, with thirty technical and political actors meeting in 5 consecutive days to discuss what should be the fundamental objectives/development axes of the PPA and to generate, assess and classify intervention programmes to achieve the objectives. Structuring objectives and programmes started by a group causal mapping session supported by the Decision Explorer DSS. Then, a multi-criteria group value model, created on-the-spot by means of the M-MACBETH DSS, helped the politicians in evaluating the overall benefit of each programme. The doability of the programmes was also appraised with MACBETH and, finally, the programmes were classified into four benefit versus doability categories defined in a $2\times 2$ strategic graph: “pearls” (programmes with high benefit value and easy to implement), “oysters” (high benefit but difficult to implement), “bread and butter” (easy to implement but of low added value) and “white elephants” (low benefit and difficult to implement). The group agreed that at least all pearls and oysters should be selected. The programmes were prioritised based on their value-for-effort and the robustness of the selection was analysed with the PROBE DSS a posteriori.     

面向O2O的Web服务描述与建模

针对现有服务描述只考虑网上Web服务功能与质量属性,忽视用户网下服务需求的弊端.基于O2O环境中用户对网上服务和网下服务的综合需求,这篇文章对传统的Web服务描述进行了扩展,构建网上网下服务描述模型,设计了网上服务和网下服务的FQoS和QoS指标体系,定义了QoS属性的量化公式,建立了服务资源本体元模型,实现了对服务资源全面整体的描述,解决了网上服务和网下服务功能质量协同的问题.具有较强的理论意义和现实意义.