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This book examines the Analytical Hierarchy Process (AHP) method, its varied uses, as well as its limitations for solving real-world scenarios. While the simplicity of the method compels users to find shortcuts to a real-world problem, it also leads to obtaining wrong results that do not represent reality. By alerting practitioners about the core necessities of a new scenario, this book helps solve this problem, as well as contribute to the field of Multicriteria Decision Making Method (MDCM).
The authors use a demonstrative, rather than a theoretical approach, and examine 30 subjects that displays the shortcomings and drawbacks of the AHP. Each one is examined in-depth, discussed, debated and reasoned, using examples, some of them numeric. The book highlights the rationality and common sense of the subjects, and in most cases, validates the criticism by showing through numerical examples, the impossibility of the AHP method to address, let alone solve real-world projects. At the conclusion of each subject, a table is built comparing the similarities and differences between the opinions of the authors and other experts, along with the respective pros and cons.
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This book is intended as a guide to and manual on modeling complex problems in Multi Criteria Decision Making (MCDM). It encourages practitioners to consider the practicalities of real-world scenarios when modeling, while at the same time providing tips and examples of how to incorporate these realities into the initial decision matrix. The goal is to help readers build a decision matrix that replicates reality as closely as possible. Once this matrix has been constructed, the Decision Maker (DM) can select from more than a hundred MCDM methods the one that best fits the requirements and conditions of the matrix. The book features cases taken from real-world scenarios, which deal with various fields, aspects, and characteristics, and are solved using the SIMUS (Sequential Interactive Modeling for Urban Systems) method. This book is a valuable tool for practitioners, researchers and students dealing with MCDM problems.
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This book examines multiple criteria decision making (MCDM) and presents the Sequential Iterative Modelling for Urban Systems (SIMUS) as a method to be used for strategic decision making. It emphasizes the necessity to take into account aspects related to real world scenarios and incorporating possible real-life aspects for modelling. The book also highlights the use of sensitivity analysis and presents a method for using criteria marginal values instead of weights, which permits the drawing of curves that depicts the variations of the objective function due to increments/decrements of criteria values. In this way, it also gives quantitative values of the objective function allowing stakeholders to perform a comprehensive risk analysis for a solution when it is affected by exogenous variables.
Strategic Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios is divided into four parts. Part 1 is devoted to exploring the history and development of the discipline and the way it is currently used. It highlights drawbacks and problems that scholars have identified in different MCDM methods and techniques. Part 2 refers to what can be done using the MCDM process. Part 3 proposes the SIMUS method as a strategic procedure to deal with MCDM problems, and addressing how to approach complicate scenarios. Part 4 is entirely devoted to support practitioners through more than 100 questions a user may ask, and their corresponding answers, as well as a collection of solved six complex real-life scenarios. The decision-making process can be a complex task, especially with multi-criteria problems. With large amounts of information, it can be an extremely difficult to make a rational decision, due to the number of intervening variables, their interrelationships, potential solutions that might exist, diverse objectives envisioned for a project, etc. The SIMUS method has been designed to offer a strategy to help organize, classify, and evaluate this information effectively.
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Covers the entire process of risk management by providing methodologies for determining the sources of engineering project risk, and once threats have been identified, managing them through: identification and assessment (probability, relative importance, variables, risk breakdown structure, etc.); implementation of measures for their prevention, reduction or mitigation; evaluation of impacts and quantification of risks and establishment of control measures. It also considers sensitivity analysis to determine the influence of uncertain parameters values on different project results, such as completion time, total costs, etc. Case studies and examples across a wide spectrum of engineering projects discuss such diverse factors as: safety; environmental impacts; societal reactions; time and cost overruns; quality control; legal issues; financial considerations; and political risk, making this suitable for undergraduates and graduates in grasping the fundamentals of risk management.
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