Defining block character

In this paper I propose a clear, efficient, and accurate method for determining if a block of contiguous buildings has an overall character. The work is needed because most contemporary design reviews presuppose the existence of visual character, but existing design principles are often too vague to make the required determination. Clarity is achieved by shifting from vague notions to a definite concept for block character: a design feature will be perceived as part of the overall character of that block if the frequency of the feature is greater than a critical threshold. An experiment suggested that the critical frequency was quite high: over 80%. A case history illustrates how the new concept of visual character could greatly increase the efficiency and accuracy of actual planning decisions.

Interactive Multiple Objective Programming Using Tchebycheff Programs and Artificial Neural Networks

A new interactive multiple objective programming procedure is developed that combines the strengths of the Interactive Weighted Tchebycheff Procedure (Steuer and Choo 1983) and the Interactive FFANN Procedure (Sun, Stam and Steuer 1993). In this new procedure, nondominated trial solutions are generated by solving Augmented Weighted Tchebycheff Programs (Steuer 1986), based on which the decision maker articulates his/her preference information by assigning "values" to these solutions or by making pairwise comparisons. The elicited preference information is used to train a feed-forward artificial neural network, which in turn is used to screen new trial solutions for presentation to decision maker in the next iteration. Computational results are reported, comparing the current procedure with the Interactive Weighted Tchebycheff Procedure and the Interactive FFANN Procedure. The results show that this new procedure yields good quality solutions

Water Supply Planning under Interdependence of Actions: Theory and Application

An ongoing water supply planning problem in the Regional Municipality of Waterloo, Ontario, Canada, is studied to select the best water supply combination, within a multiple-objective framework, when actions are interdependent. The interdependencies in the problem are described and shown to be essential features. The problem is formulated as a multiple-criteria integer program with interdependent actions. Because of the large number of potential actions and the nonconvexity of the decision space, it is quite difficult to find nondominated subsets of actions. Instead, a modified goal programming technique is suggested to identify promising subsets. The appropriateness of this technique is explained, and the lessons learned in applying it to the Waterloo water supply planning problem are described

An Integrated Probability-Based Approach for Multiple Response Surface Optimization

Nearly all real life systems have multiple quality characteristics where individual modeling and optimization approaches can not provide a balanced compromising solution. Since performance, cost, schedule, and consistency remain the basics of any design process, design configurations are expected to meet several conflicting requirements at the same time. Correlation between responses and model parameter uncertainty demands extra scrutiny and prevents practitioners from studying responses in isolation. Like any other multi-objective problem, multi-response optimization problem requires trade-offs and compromises, which in turn makes the available algorithms difficult to generalize for all design problems. Although multiple modeling and optimization approaches have been highly utilized in different industries, and several software applications are available, there is no perfect solution to date and this is likely to remain so in the future. Therefore, problem specific structure, diversity, and the complexity of the available approaches require careful consideration by the quality engineers in their applications

Managerial judgment and forecast combination: An experimental study

This paper examines the role of managerial judgment in forming a final forecast, or judging the achievability of a critical level of sales, when multiple forecasts or opinions are available to the decision maker. Several factors that can help improve the quality of human intervention are identified and incorporated in a decision aid. Experimental results show that aided combination can help the decision maker exploit her relevant private information and mitigate the generally observed negative effects of human intervention. Further, the results suggest that emphasizing expected sales, even when the organization is primarily interested in go/no-go decisions, helps improve performance. Several suggestions for future research are presented.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47133/1/11002_2004_Article_BF00993954.pd

Sequential decision making with adaptive utility

Decision making with adaptive utility provides a generalisation to classical Bayesian decision theory, allowing the creation of a normative theory for decision selection when preferences are initially uncertain. The theory of adaptive utility was introduced by Cyert & DeGroot [27], but had since received little attention or development. In particular, foundational issues had not been explored and no consideration had been given to the generalisation of traditional utility concepts such as value of information or risk aversion. This thesis addresses such issues. An in-depth review of the decision theory literature is given, detailing differences in assumptions between various proposed normative theories and their possible generalisations. Motivation is provided for generalising expected utility theory to permit uncertain preferences, and it is argued that in such a situation, under the acceptance of traditional utility axioms, the decision maker should seek to select decisions so asto maximise expected adaptive utility . The possible applications of the theory forsequential decision making are illustrated by some small-scale examples, including examples of relevance within reliability theory

Stability of risk attitude across choice contexts and frames

Abstract from public.pdfWe report the results of the large-scale study of risk attitude demonstrating substantial heterogeneity both between and within decision makers across three risky choice contexts: financial, mortality and climate change. We use a p-additive model of risk to classify decision makers according to their risk attitude in each context and frame (i.e., gains or losses). Our results indicate that while some decision makers exhibit stable risk preferences across contexts and decision frames, many others have risk preferences which vary depending on the choice environment. We find almost no evidence of the reflection effect for individual DMs or in choice data aggregated across DMs. We discuss the implications for economic and psychological research and modeling of risk attitudes, emphasizing that any one-size-fits-all approach to risk attitude such as assuming risk neutrality or risk aversion is unlikely to accurately describe the choice behavior of decision makers.Includes biblographical reference

Multiple Objective Programming Support

This paper gives a brief introduction into multiple objective programming support. We will overview basic concepts, formulations, and principles of solving multiple programming problems.To solve those problems requires the the intervention of a decision-maker. That's why behavioral assumptions play an important role in multiple objective programming. Which assumptions are made affects which kindof support is given to adecision maker. We will demonstrate how a free search type approach can be used to solve multiple objective programming problems

User-Oriented Methodology and Techniques of Decision Analysis and Support

This volume contains 26 papers selected from Workshop presentations. The book is divided into two sections; the first is devoted to the methodology of decision analysis and support and related theoretical developments, and the second reports on the development of tools -- algorithms, software packages -- for decision support as well as on their applications. Several major contributions on constructing user interfaces, on organizing intelligent DSS, on modifying theory and tools in response to user needs -- are included in this volume