Interactive Fuzzy Random Two-level Linear Programming through Fractile Criterion Optimization

This paper considers two-level linear programming problems involving fuzzy random variables. Having introduced level sets of fuzzy random variables and fuzzy goals of decision makers, following fractile criterion optimization, fuzzy random two-level programming problems are transformed into deterministic ones. Interactive fuzzy programming is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

This paper considers linear programming problems (LPPs) where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables). New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments

Satisficing solutions for multiobjective stochastic linear programming problems

Multiobjective Stochastic Linear Programming is a relevant topic. As a matter of fact, many real life problems ranging from portfolio selection to water resource management may be cast into this framework. There are severe limitations in objectivity in this field due to the simultaneous presence of randomness and conflicting goals. In such a turbulent environment, the mainstay of rational choice does not hold and it is virtually impossible to provide a truly scientific foundation for an optimal decision. In this thesis, we resort to the bounded rationality and chance-constrained principles to define satisficing solutions for Multiobjective Stochastic Linear Programming problems. These solutions are then characterized for the cases of normal, exponential, chi-squared and gamma distributions. Ways for singling out such solutions are discussed and numerical examples provided for the sake of illustration. Extension to the case of fuzzy random coefficients is also carried out.Decision Science

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Decision support tools for environmentally conscious chemical process design

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1999.Electronic version available online."September 2000."Includes bibliographical references.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.The environment has emerged as an important determinant of the performance of the modern chemical industry. Process engineering in the 21st century needs to evolve to include environmental issues as part of the design objectives, rather than as constraints on operations. A frequently cited objection to the use of quantitative indicators of environmental performance in product and process design is that the underlying data are too uncertain for the numbers to have any real meaning. This thesis demonstrates that explicit incorporation of uncertainties allows bounds to be established on the confidence of decisions made on the basis of uncertain indicators. The examples provided show that large uncertainties in indicators used to assess environmental performance do not necessarily imply uncertainty in decision-making. A series of computer-aided decision making tools have been developed to decrease the barriers to the use of environmental valuation functions in routine design activities. These tools include: uncertainty propagation of relative performance measures, a spreadsheet-based fate, transport and exposure model for chemicals, an information content chart for assessing the quality of uncertain indicators, a screening procedure to identify the most important structural and parametric uncertainties in multimedia exposure models,a process by product input-output life cycle assessment method to generate correlated distributions of unit environmental indicators, an extension of the deterministic equivalent modeling method for the generation of spreadsheet based polynomial chaos expansion metamodels of process flowsheet models, and a database for managing uncertain parameters used in environmental valuation models. Case studies are presented to help the reader in learning the use of the tools. The tools are also applied to an analysis of the U.S. toxics release inventory, in which confidence bounds are developed for the trends in impacts and the contributions of industrial sectors and specific chemical compounds to overall potential impact. Although the tools were developed bearing in mind the need for methods to evaluate the environmental performance of chemical process design alternatives, the ideas can be applied to any decision context in which there are significant uncertainties in the parameters of the objective function.by José Alejandro Cano Ruiz.Ph.D

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

A total quality management (TQM) strategic measurement perspective with specific reference to the software industry

The dissertation aims to obtain an integrated and comprehensive perspective on measurement issues that play a strategic role in organisations that aim at continuous quality improvement through TQM. The multidimensional definition of quality is proposed to view quality holistically. The definition is dynamic, thus dimensions are subject to evolution. Measurement of the quality dimensions is investigated. The relationship between quality and cost, productivity and profitability respectively is examined. The product quality dimensions are redefined for processes. Measurement is a strategic component ofTQM. Integration of financial measures with supplier-; customer-; performance- and internal process measurement is essential for synergism. Measurement of quality management is an additional strategic quality dimension. Applicable research was integrated. Quantitative structures used successfully in industry to achieve quality improvement is important, thus the quality management maturity grid, cleanroom software engineering, software factories, quality function deployment, benchmarking and the ISO 9000 standards are briefly described. Software Metrics Programs are considered to be an application of a holistic measurement approach to quality. Two practical approaches are identified. A framework for initiating implementation is proposed. Two strategic software measurement issues are reliability and cost estimation. Software reliability measurement and modelling are introduced. A strategic approach to software cost estimation is suggested. The critical role of data collection is emphasized. Different approaches to implement software cost estimation in organisations are proposed. A total installed cost template as the ultimate goal is envisaged. An overview of selected software cost estimation models is provided. Potential research areas are identified. The linearity/nonlinearity nature of the software production function is analysed. The synergy between software cost estimation models and project management techniques is investigated. The quantification aspects of uncertainty in activity durations, pertaining to project scheduling, are discussed. Statistical distributions for activity durations are reviewed and compared. A structural view of criteria determining activity duration distribution selection is provided. Estimation issues are reviewed. The integration of knowledge from dispersed fields leads to new dimensions of interaction. Research and practical experience regarding software metrics and software metrics programs can be successfully applied to address the measurement of strategic indicators in other industries.Business ManagementD. Phil. (Operations Research