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.     

Near‐Misses and Future Disaster Preparedness

Disasters garner attention when they occur, and organizations commonly extract valuable lessons from visible failures, adopting new behaviors in response. For example, the United States saw numerous security policy changes following the September 11 terrorist attacks and emergency management and shelter policy changes following Hurricane Katrina. But what about those events that occur that fall short of disaster? Research that examines prior hazard experience shows that this experience can be a mixed blessing. Prior experience can stimulate protective measures, but sometimes prior experience can deceive people into feeling an unwarranted sense of safety. This research focuses on how people interpret near‐miss experiences. We demonstrate that when near‐misses are interpreted as disasters that did not occur and thus provide the perception that the system is resilient to the hazard, people illegitimately underestimate the danger of subsequent hazardous situations and make riskier decisions. On the other hand, if near‐misses can be recognized and interpreted as disasters that almost happened and thus provide the perception that the system is vulnerable to the hazard, this will counter the basic “near‐miss” effect and encourage mitigation. In this article, we use these distinctions between resilient and vulnerable near‐misses to examine how people come to define an event as either a resilient or vulnerable near‐miss, as well as how this interpretation influences their perceptions of risk and their future preparedness behavior. Our contribution is in highlighting the critical role that people's interpretation of the prior experience has on their subsequent behavior and in measuring what shapes this interpretation.     

The impact of learning opportunities and decision authority on occupational health

In an investigation of 418 employees in the Norwegian Postal Service, employees with high learning opportunities and high decision authority were found to be better off on psychological functioning, health and organizational outcome variables than employees with low scores on these variables. Decision authority and learning opportunities had specific and independent impact on subjective health, psychological functioning, coping style and organizational outcome variables. There were, however, also interaction effects between demands, learning opportunities, and decision authority on subjective health. Learning opportunities and decision authority were operationalized with a questionnaire, supplemented with questions on the opportunities to learn skills beyond the present job situation. It is suggested that this is a particularly important dimension for coping with the present day rapid changes in working life, where the objective for many workers will be to broaden their repertoire and competence to increase their flexibility in the labour market.     

Incorporating quality into data envelopment analysis of nursing home performance: A case study

When using data envelopment analysis (DEA) as a benchmarking technique for nursing homes, it is essential to include measures of the quality of care. We survey applications where quality has been incorporated into DEA models and consider the concerns that arise when the results show that quality measures have been effectively ignored. Three modeling techniques are identified that address these concerns. Each of these techniques requires some input from management as to the proper emphasis to be placed on the quality aspect of performance. We report the results of a case study in which we apply these techniques to a DEA model of nursing home performance. We examine in depth not only the resulting efficiency scores, but also the benchmark sets and the weights given to the input and output measures. We find that two of the techniques are effective in insuring that DEA results discriminate between high and low quality performance.     

Statisticians Can Matter

Statisticians fall far short of their potential as guides to enlightened decision making in business. Two important explanations are: (1) Decision makers are often more easily convinced by concrete examples, however fragmentary and misleading, than by competent statistical analysis. (2) The effective use of statistics in the process of decision making requires hard thinking by decision makers, thinking that cannot be delegated entirely to the statistical specialist. Modern developments in interactive statistical computing may help to reduce the force of these limitations on exploitation of statistics; used properly, computing can encourage, almost force, the student or business user of statistics to think statistically.     

缩短供应链多阶响应周期的物流模式研究

为了满足最终客户的多样化、及时化的需求,供应链的物流模式成了缩短供应链多阶响应周期的一个重要的研究领域。对比传统的物流模式,快速响应的供应链物流模式的主要改进点在制造商及其以下的节点企业的物流上。四种物流模式对于缩短供应链最终用户的响应周期有极大的意义和作用,它们是:基于制造商的直销模式、以批发商为改进点的零售支持型批发物流和区域零售支持型综合批发物流,以及以零售商为切入点的产销联盟的物流模式,并且它们各自不同的适用范围取决于供应链的运作特点和行业特征。     

Global Robustness with Respect to the Loss Function and the Prior

We propose a class [I,S] of loss functions for modeling the imprecise preferences of the decision maker in Bayesian Decision Theory. This class is built upon two extreme loss functions I and S which reflect the limited information about the loss function. We give an approximation of the set of Bayes actions for every loss function in [I,S] and every prior in a mixture class; if the decision space is a subset of , we obtain the exact set.     

经济效益综合评价中的简单方法──序时多属性决策方法

本文对序时多属性决策方法进行了研究,针对工业经济效益的综合评价,提出了二个简单的方法,它以简单加权法(SAW)的基础,能够自动确定各评价目标间的加权系数,对决策方案和评价目标没有任何数量要求和限制,决策结果不具有主观随意性,运用该方法对全国部分省市经济效益进行综合评价的结果表明；它与运用非序时多属性决策方法计算的结果基本一致,而后者的计算量大大多于前者。     

Decision Making Under Risk: A Comparison of Bayesian and Fuzzy Set Methods

A classical decision problem is considered where a decision maker is to choose one of a number of actions each offering different consequences. The outcome from a choice of action is uncertain because it depends on the existing state of Nature. Also, the outcome, once an action and state of Nature are specified, may be a vector or a random vector. The decision maker employs both Bayesian methods and fuzzy set techniques to handle the uncertainties. The decision maker is also allowed to use multiple, possibly conflicting, goals in order to determine his best strategy. The Bayesian method produces a set of undominated strategies to choose from, whereas the fuzzy set technique usually produces a unique optimal strategy.     

地州市领导科学决策的原则和方法

科学决策方法是科学决策的重要组成部分,它是实现科学决策目标重要的"桥"和"船",对实现决策目标具有重要的保证和服务作用。科学决策的方法虽然很多,但对领导干部而言最主要的是要学习和掌握调查研究的方法,群众路线的方法,专家评估的方法,民主决策和程序决策的方法。