Multi-Criteria Decision Analysis

Case Studies in Engineering and the Environment

Igor Linkov, Emily Moberg, Benjamin D. Trump, Boris Yatsalo, Jeffrey M. Keisler

• Publisher: CRC Press
• Year: 2020
• Print ISBN: 9780367345334
• eBook ISBN: 9781000177909
• Edition: 2
• Topic: Business
• Subtopic: Environmental Law
• Index: Business

Decision analysis has become widely recognized as an important process for translating science into management actions. With climate change and other systemic threats as driving forces in creating environmental and engineering problems, there is a great need for understanding decision making frameworks through a case-study based approach. Management of environmental and engineering projects is often complicated and multidisciplinary in scope and nature, thus issues that arise can be difficult to solve analytically. Multi-Criteria Decision Analysis: Case Studies in Engineering and the Environment provides detailed description of MCDA methods and tools and illustrates their applications through case studies focused on sustainability and system engineering applications.

New in the Second Edition:

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• Addresses current and emerging environmental and engineering problems

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• Includes seven new case studies to illustrate different management situations applicable at the international level

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• Builds on real case studies from recent and relevant environmental and engineering management experience

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• Describes advanced MCDA techniques and extensions used by practitioners

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• Provides corresponding decision models implemented using the DECERNS software package

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• Gives a more holistic approach to teaching MCDA methodology with a focus on sustainable solutions and adoption of new technologies, including nanotechnology and synthetic biology

Given the novelty and inherent applicability of this decision-making framework to the environmental and engineering fields, a greater number of teaching tools for this topic need to be made available. This book provides those teaching tools, covering the breadth of the applications of MCDA methodologies with clear explanations of the MCDA process. The case studies are implemented in the DECERNS software package, allowing readers to experiment and explore and to understand the full process by which environmental managers assess these problems.

This book is a great resource for professionals and students seeking to learn decision analysis techniques and apply similar frameworks to environmental and engineering projects

Part I

Multi-Criteria Decision Analysis: Methods and Applications

1

Introduction to Multi-Criteria Methods

Background

Think about the most recent time you encountered an “environmental issue” in the news. In the first edition of this book, we highlighted natural gas drilling controversies, the aftermath of the Tohoku tsunami in Japan, and the battle over the US Environmental Protection Agency’s potential regulation of carbon emissions as examples of the issues you might have seen. In the intervening years, the environmental issues have not stopped; climate change (in)action, pesticide regulation, air quality issues from burning crops, algal blooms, and taxes on plastic bag or straw usage have all been major news stories across the world. These stories are often longer than a single article; coverage of events can last months. The articles will quote politicians, scientists, health care professionals, business leaders, and affected citizens.

The multiple voices and viewpoints showcased in these articles highlight one of the hallmarks of environmental decisions—they often involve complex science, many stakeholders, and potential solutions which need to be judged against many different criteria in order to be fully compared.

Unfortunately, our basic human tendency is to simplify such complicated decisions and situations until they are more manageable, which results in the loss of information about the problem, loss of information about other viewpoints, and loss of information about uncertainty; in essence, we struggle to incorporate all the available information to make a fully informed choice. The result can be controversies and issues that rage on for months and years without satisfactory resolution.

Unaided, we are quite bad at making complex decisions (McDaniels et al. 1999), and environmental decisions often fall into this complex category. In environmental problems, the expected inputs include modeling or monitoring data, risk analysis, cost or cost–benefit analysis, and stakeholders’ preferences; integrating this information is a major challenge (Linkov and Ramadan 2004). This integration process can be opaque and seen as unfair, especially when stakeholder preferences are not dealt with in a manner that is perceived as objective.

MCDA Methods

One type of method that has been used increasingly in many fields, including environmental decision-making, is Multi-Criteria Decision Analysis (MCDA). The method allows for preferences and performance about different management alternatives to be assessed in a clear, formal way that is both mathematically rigorous and transparent to stakeholders. The basic outline for an MCDA which will be followed in this book is:

1. Problem Identification: The problem is defined in terms of relevant stakeholders and overall structure but is not yet described quantitatively.
2. Problem Structuring: The problem is fleshed out by defining alternatives and criteria. Alternatives—the potential management options—are defined. The alternatives are what a decision maker is deciding among. Criteria—the set of properties (such as cost or environmental impact) that describe alternative performance—are also established. The criteria are essentially what the decision maker values; performance against these criteria is what is used to decide among alternatives.
3. Model Assessment/Building: The alternatives and criteria are given numeric values. The alternatives are scored against the criteria (e.g. Plan A may cost $2,000, so its score for cost may be “$2,000” or “high” depending on our setup). Decision makers (or stakeholders) also weight criteria according to the value or importance they put on that criterion. This gives us the information how well does each alternative perform on each criterion and how much do we care about performance on each criterion.
4. Model Application: The inputs—the criteria weights and alternative scoring—are combined in an MCDA model and output which alternative is best according to the data given. Each model works in a slightly different way (as will be explained later in this chapter) but essentially combines the preference and scoring information for each alternative. The output can range from an ordered list of alternatives to a set of probabilities that an alternative will be well accepted or not.
5. Planning and Extension: Once the model has been run, the output can be used to make decisions or inform further planning.

As we alluded to in the Model Application step, there are many types of MCDA models. This book will explore three basic categories of models: Multi-Attribute Utility Theory (MAUT), Analytical Hierarchy Process (AHP), and outranking. Understanding the mechanics of how each method combines the preferences and scoring is very important before applying them; Belton and Stewart (2002) is an excellent resource for theoretical and comparative discussions of the models. A briefer description of the models is given below.

MAUT

Multi-Attribute Utility Theory or Multi-Attribute Value Theory (MAUT and MAVT respectively; they are often used interchangeably) resolves the disparate units (cost, environmental impact, etc.) of our criteria into a utility or value so comparison among alternatives’ scores can occur. We also elicit information about how important each criterion is relative to the others. With these two pieces of information, we can now combine the preferences (weights of criteria) with the scores (which have been transformed into a single type of unit, the value or utility) to make a coherent decision.

Methodologically, the critical step is eliciting or defining the value functions. From...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Foreword
• Preface
• Acknowledgments
• Authors
• Part I Multi-Criteria Decision Analysis: Methods and Applications
• Part II MCDA Methods in Depth: Sediment Management
• Part III MCDA Application in Depth: Nanomaterials
• Part IV MCDA Application Case Studies
• Appendix
• Index