A robust ranking method extending ELECTRE III to hierarchy of interacting criteria,imprecise weights and stochastic analysis

A great majority of methods designed for Multiple Criteria Decision Aiding (MCDA) assume that all assessment criteria are considered at the same level, however, decision problems encountered in practice often impose a hierarchical structure of criteria. The hierarchy helps to decompose complex decision problems into smaller and manageable subtasks, and thus, it is very attractive for computational efficiency and explanatory purposes. To handle the hierarchy of criteria in MCDA, a methodology called Multiple Criteria Hierarchy Process (MCHP), has been recently proposed. MCHP permits to consider preference relations with respect to a subset of criteria at any level of the hierarchy. Here, we propose to apply MCHP to the ELECTRE III ranking method adapted to handle three types of interaction effects between criteria: mutual-weakening, mutual-strengthening and antagonistic effect. We also involve in MCHP an imprecise elicitation of criteria weights, generalizing a technique called the SRF method. In order to explore the plurality of rankings obtained by the ELECTRE III method for possible sets of criteria weights, we apply the Stochastic Multiobjective Acceptability Analysis (SMAA) that permits to draw robust conclusions in terms of rankings and preference relations at each level of the hierarchy of criteria. The novelty of the whole methodology consists of a joint consideration of hierarchical assessments of alternatives performances on interacting criteria, imprecise criteria weights, and robust analysis of ranking recommendations resulting from ELECTRE III. An example regarding the multiple criteria ranking of some European universities will show how to apply the proposed methodology on a decision problem.     

Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing

Abstract

A central objective of empirical research on treatment response is to inform treatment choice. Unfortunately, researchers commonly use concepts of statistical inference whose foundations are distant from the problem of treatment choice. It has been particularly common to use hypothesis tests to compare treatments. Wald’s development of statistical decision theory provides a coherent frequentist framework for use of sample data on treatment response to make treatment decisions. A body of recent research applies statistical decision theory to characterize uniformly satisfactory treatment choices, in the sense of maximum loss relative to optimal decisions (also known as maximum regret). This article describes the basic ideas and findings, which provide an appealing practical alternative to use of hypothesis tests. For simplicity, the article focuses on medical treatment with evidence from classical randomized clinical trials. The ideas apply generally, encompassing use of observational data and treatment choice in nonmedical contexts.     

高校教学考试现状分析与改革思路

高校教学考试是高校教学工作的重要环节,是检测、鉴定、衡量师生教学质量的主要手段。教学考试在教学中具有教育、管理、导向、激励的积极作用,同时在制度、方法、监管、评价、时间安排等方面也存在一些负面问题。分析教学考试利弊,扬长避短,改革创新,营造科学适宜的教学考试机制,对撬动高校教学改革,提高教学质量,培养全面发展的合格大学生具有至关重要的意义。     

双电机驱动自同步振动磨动力响应研究

以双电机驱动自同步振动磨为研究对象,对其进行简化处理,建立力学模型。通过对其施加X,y方向的简谐激 振力,建立无阻尼系统强迫振动和有阻尼系统强迫振动的数学模型,在此基础上,确定Rayleigh阻尼的常数α和β,利用 有限元ANSYS软件进行瞬态动力学分析,研究其在动载荷作用下的变形情况。研究结果表明：在工况频率16 Hz下,节 点运动轨迹更接近圆形,距理想粉碎效果的圆形轨迹较近,粉碎效果较好,进入稳定期的时间较快;在共振频率42 Hz 下,节点轨迹振幅更大,进入稳定期较慢,阻尼对振动的衰减作用较强;不同阻尼比对振动的衰减作用成正比关系。因 此,可以通过控制阻尼比等参数获得更有利的研磨效果,提高研磨效率。     

南京中山植物园游憩功能满意度评价研究

随着植物园"旅游经济"的发展,植物园在承担植物科学研究及科普功能的同时,也成为公众日常休闲的重要绿地。本文选取南京中山植物园作为研究对象,建立评价体系并运用模糊综合评价法对游客满意度进行研究,探寻影响植物园游憩功能的显著因子,为未来植物园规划设计提供参考。结果表明:游客对南京中山植物园的游憩功能达到基本满意水平。其中,植物物种多样性、景区分布、建筑景观、声景观的满意度较高,滨水景观的满意度评价值较低。通过Pearson相关系数发现植物色彩丰富度、科普场所、科普内容是影响游客满意度的显著因子。运用IPA图对16项评价因子进行重要度-满意度分析,并对各象限内的因子提出改进方向。最后基于游憩功能满意度评价结果,提出改进策略:加大对植物园休息设施、卫生设施、娱乐设施和商业服务设施的投入;更新科普方式,增添特色游憩主题园区;完善现有道路体系,增强对北部专类园的可达性;增加色叶植物的种类、提高色彩丰富度等。以期为中山植物园游憩功能的优化及其他植物园的规划设计提供借鉴。     

Notes and Communications “A DECISION THEORY EXAMPLE IN FOOTBALL”: A COMMENT*

Janssen and Daniel analyzed the choice between a one- or a two-point conversion for a particular game situation in college football. Their decision criteria was maximum expected utility based on a von Neumann-Morgenstern utility function defined over the games outcomes. An alternative approach based on a stochastic dominance criterion is presented that does not rely on knowledge of the relative importance of tying vs. winning; rather, it relies on a notion of consistency in the sequential problem.     

A NOTE ON HOLDING COSTS AND LOT-SIZE ERRORS

This note examines the sensitivity of the basic economic-order-quantity inventory model to lot-size errors when holding costs are assumed to be a strictly increasing (though not necessarily linear) function of average inventory. In particular, we show that the penalty associated with ordering either too much or too little is a function not only of the size of the error but of the shape of the holding-cost curve as well. We demonstrate that, under certain conditions, even relatively small lot-size errors can be extremely costly.     

Concepts,Theory, and Techniques PRINCIPLES OF MULTIOBJECTIVE OPTIMIZATION*

This paper attempts to isolate and analyze the principal ideas of multiobjective optimization. We do this without casting aspersions on single-objective optimization or championing any one multiobjective technique. We examine each fundamental idea for strengths and weaknesses and subject two—efficiency and utility—to extended consideration. Some general recommendations are made in light of this analysis. Besides the simple advice to retain single-objective optimization as a possible approach, we suggest that three broad classes of multiobjective techniques are very promising in terms of reliably, and believably, achieving a most preferred solution. These are: (1) partial generation of the efficient set, a rubric we use to unify a wide spectrum of both interactive and analytic methods; (2) explicit utility maximization, a much-overlooked approach combining multiattribute decision theory and mathematical programming; and (3) interactive implicit utility maximization, the popular class of methods introduced by Geoffrion, Dyer, and Feinberg [24] and extended significantly by others.     

STOCHASTIC COST-VOLUME-PROFIT ANALYSIS IN A COMPETITIVE OLIGOPOLY

Previous stochastic cost-volume-profit (CVP) models have assumed that the firm was operating under either perfect competition or monopolistic conditions. This paper presents a stochastic CVP model applicable to oligopolistic competition. Each firm is assumed to maximize a linear function of the expected value and the standard deviation of its random profits. The result is a game-theoretic model that is solved using the concept of a Nash equilibrium. The results of the model are used to examine a firm's competitive strength. The model can be easily modified to accommodate a measure of risk based on the capital asset pricing theory.     

A DECISION THEORY EXAMPLE IN FOOTBALL

In the 1967 Harvard-Cornell football game, Harvard was ahead 14–0 late in the game when Cornell scored two touchdowns. On both occasions, Cornell tried and failed on the two-point conversion attempt and lost the game 14–12. Postgame arguments were divided on the merits of Cornell's strategy. For this frequently occurring scenario in college football, we derive a maximum expected utility decision rule for the decision of kicking versus running/passing based on the relative utility of a win, a tie, or a loss and the probabilities of success with a kick as opposed to a run/pass.