A fuzzy multiple attribute utility model for intelligent building assessment

Multi-Attribute Utility Theory (MAUT) is an evaluation scheme which is very popular by decision makers for evaluating their judgments. According to MAUT, the overall evaluation U(x) of an object x is defined as a weighted addition of its evaluation with respect to its relevant value dimensions. The recent years have witnessed a huge concentration and interest in intelligent buildings’ performance that is increasingly evidenced in building design and construction. Intelligent buildings (IBs) are also under assessment according to their IB related characteristics and actual circumstances. For this aim, in this paper a fuzzy multiple attribute utility model for intelligent building assessment is proposed and three alternative intelligent buildings for a business center in Istanbul are evaluated

Integrating Cost as an Independent Variable Analysis with Evolutionary Acquisition - A Multiattribute Design Evaluation Approach

Guidance from the Under Secretary of Defense for Acquisition, Technology, and Logistics (USD(AT&L)) requires 100 percent of defense programs to incorporate cost as an independent variable (CAIV) and evolutionary acquisition (EA) plans within their management baselines. Historically, these two concepts have been implemented independent of one another. In reality, CAIV and EA are tightly coupled, Integration of these two initiatives enables warfighters and developers to better allocate constrained resources, respond to fluctuations in program funding, and plan for future development activities. This research creates a decision tool to assist the DoD acquisition community in satisfying the intent of the USD(AT&L) guidance. Using multiattribute design evaluation techniques, a core CAIV model is formulated. Next, the core model is expanded to incorporate the dominant features of EA. The expanded model seeks to optimize overall utility across a horizon of multiple development increments. Additionally, technical risk factors are integrated to discount the realized level of attainment for design attributes. Using a DoD command and control system development as the case study, the fully formulated CAIV/EA model is implemented and in a PC spreadsheet. An optimization application solves the mathematical program for a series of cost constraints. The resulting data are collected and translated into a variety of graphics. Sensitivity analysis is performed to understand the response caused by variations in the model\u27s parameters. Model limitations are discussed and recommendations for further investigation are presented

Robustness of Multiple Objective Decision Analysis Preference Functions

This research investigated value and utility functions in multiobjective decision analysis to examine the relationship between them in a military decision making context. The impact of these differences was examined to improve implementation efficiency. The robustness of the decision model was examined with respect to the preference functions to reduce the time burden imposed on the decision maker. Data for decision making in a military context supports the distinction between value and utility functions. Relationships between value and utility functions and risk attitudes were found to be complex. Elicitation error was significantly smaller than the difference between value and utility functions. Risk attitudes were generally neither constant across the domain of the evaluation measure nor consistent between evaluation measures. An improved measure of differences between preference functions, the weighted root means square, is introduced and a goodness of fit criterion established. An improved measure of risk attitudes employing utility functions is developed. Response Surface Methodology was applied to improve the efficiency of decision analysis utility model applications through establishing the robustness of decision models to the preference functions. An algorithm was developed and employs this information to provide a hybrid value-utility model that offers increased elicitation efficiency

Contractor selection using the multiattribute utility theory

Literature and past research suggests that one of the reasons for the poor performance ofthe construction industry is due to the inappropriateness of the awarded contractor. Inorder to ensure a successful completion of a project, a comprehensive and carefulassessment of contractors data in a prequalification stage is required. Appointing anappropriate contractor to carry out the construction work, therefore, becomes one of themost important tasks to ensure the success of a project.In this thesis the author has made a preliminary survey to investigate the bidding processcurrently used in the construction industry through literature survey, extensive interviewswith the construction professionals and an industry wide questionnaire. The investigationhas focused on the procedures of prequalification and bids evaluation, it also covers thelist of criteria considered for selecting contractors in prequalification and bid evaluationstages.The thesis investigated the perceived relationship between contractor selection criteria(CSC) currently in use and predominant project success factors (PSF) in terms of time,cost and quality involving a sample of experienced construction professionals. This research is based on the premise that selection should concentrate on determiningcontractor potential for achieving project goals in terms of time, cost and quality. Thestudy presented a quantitative technique to combine the contractor data in terms of thesegoals. The study also presented an evaluation strategy that involves the consideration bothof the client goals as ends and contractor data as the means, the strategy based on thernultiattribute utility theory for the frnal selection or rank ordering of the contractors. Theselection is ultimately based on the preferences and the attitude of the decision makertoward risk.A real case study was used to validate the proposed methodology for contractorprequalification.The benefit of this work is that it provides a means using the PERT methodology toincorporate uncertainty andlor imprecision associated with the assessment of contractorsdata, this all in terms of the ultimate project success factors of time, cost, and quality.The utility technique proposed should help clients in selecting contractors and thecontractors themselves for selecting sub-contractors in offering a means of broadeningtheir analysis of tenderers beyond that of simply relying on tender values. It also alertscontractors to the importance of increasing their ability to satisfy the needs of the clients interms of their ultimate project goals

Disassembly and Reassembly Sequence Planning Tradeoffs Under Uncertainty for Product Maintenance

The problem addressed in this paper is disassembly sequence planning for the purposes of maintenance or component upgrading, which is an integral part of the remanufacturing process. This involves disassembly, component repair or replacement, and reassembly. Each of these steps incurs cost as well as the probability of damage during the process. This paper presents a method for addressing these tradeoffs, as well as the uncertainty associated with them. A procedure for identifying the best sequence of disassembly operations for maintenance and/or component upgrade is presented. It considers both disassembly and reassembly costs and uncertainties. Graph-based integer linear programming combined with multi-attribute utility analysis is employed to identify the best set of tradeoffs among (a) disassembly time (and resulting cost) under uncertainty, (b) the probability of not incurring damage during disassembly, (c) reassembly time (and resulting cost), and (d) the probability of not incurring damage during reassembly. An example of a solar heating system is used to illustrate the method

Decision Analysis with Multiple Conflicting Objectives, Preferences and Value Tradeoffs

This working paper is the manuscript for a book titled "Decision Analysis with Multiple Conflicting Objectives: Preferences and Value Tradeoffs" being published by John Wiley and Sons, New York. It is being distributed now in very limited number prior to formal publication both (1) to facilitate the use of these results within the IIASA projects, and (2) to elicit comments on their content. The work reported here began over five years ago when Ralph L. Keeney was affiliated with the Massachusetts Institute of Technology and Howard Raiffa was at Harvard University. The finalization of this work has taken place at IIASA where our interactions with various members of the applied projects has helped to make the presentation more useful to potential practitioners. Efforts are now beginning to utilize the theories and procedures outlined in this book on the problems being addressed by the applied projects of IIASA. We plan to report on these developments in the various IIASA publications in the near future

Supporting Technology Development Evaluation with Multiple Attribute Analysis and Fuzzy Decision Analysis

In many industrialized countries technology development programs have become one of the main policy measures for enhancing future economic growth. The choices between alternative programs have turned out to be highly unstructured decisions which are very difficult to support. In this study a process of evaluation system design is developed. The approach developed disaggregates the problem into pieces. First, the objectives of the organization or activity have to be defined. Secondly, the properties of the objective set are analyzed using multiple attribute utility analysis and fuzzy decision analysis. The final system design starts with defining the required characteristics of the system. The system is composed of three separate subsystems interacting with each other. The prior evaluation system structures the prior evaluation process and defines the evaluation procedures, objectives, and responsibilities. The simulation model utilizing the mathematical theories mentioned above supports the intuitive evaluation process. The performance evaluation system measures the performance of the organization, provides a check for the prior evaluations, and establishes a learning process in which the organization utilizes its own experience for orientation in the future. The developed processes and systems are applied to the evaluation of technology development programs and projects at the Technical Research Center of Finland