Jason Papathanasiou - Multiple Criteria Decision Aid: Methods, Examples and Python Implementations

Aims and Scope

Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics, engineering, medicine, economics and other sciences.

The series Springer Optimization and Its Applications aims to publish state-of-the- art expository works (monographs, contributed volumes, textbooks) that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization (convex and nonconvex), network flow problems, stochastic optimization, optimal control, discrete optimization, multi-objective programming, description of software packages, approximation techniques and heuristic approaches.

More information about this series at http://www.springer.com/series/7393

This Springer imprint is published by the registered company Springer Nature Switzerland AG

The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

I am particularly happy to write this foreword, for several reasons. First, I appreciate the work done by Jason Papathanasiou and Nikolaos Ploskas to propagate multicriteria decision aid in classes, to make students think about the consequences of their decisions, and to promote the use of multicriteria methods in actual decision problems. Inspired by the famous quote by the French writer and politician Andr Malraux, I am sure that the twenty-first century will be ethical or it will not be. Indeed, ethics is essential for the survival of our world. Decisions shape our future. Decisions are often difficult to make. Decisions can be good or bad. Decisions have often been poorly made, especially during the last decades. Today, we can observe the resulting crises all around the world. Many decisions are bad because they rely on a single, often economic (cost or profit) criterion. They can be made on a qualitative basis (experience, expertise, etc.) or using unicriterion optimization models and methods. Anyway, they usually fail because they are shortsighted and biased: they do not take into account all the stakeholders, all the objectives that are essential for our future. As a crucial example, achieving sustainable development is impossible with a unicriterion approach. It calls for a multicriteria approach encompassing economic as well as social and environmental objectives. Multicriteria decision aid can help us to achieve better, more sustainable decisions. This book is an important step toward a more widespread use of multicriteria models and methods.

A second point is that the authors do not focus on a single method but rather review different multicriteria methods. It is important to understand that there exists no ideal multicriteria decision-making method. Instead many different methods have been proposed over the last 50 years. Each of them has advantages and limits. Each of them is making specific assumptions about the type of the decision problem and about the preferences of the decision makers. Choosing the right method also depends on the problem at hand: the availability of data, the quality of data, the type and number of decision makers, the requirements of the different stakeholders, etc. All these parameters have an impact on the choice of an appropriate method. With this in mind, the authors present the principles and the characteristics of six families of methods. This set of methods is not exhaustive; other interesting methods exist as well. However, the choice that they have made reflects the different types of methods currently available as good as possible.

TOPSIS and VIKOR are two compensatory aggregation methods that have been widely used during the recent years. They are simple to use and rather straightforward to understand. PROMETHEE is a well-known outranking method. It allows for partial compensation between criteria and has many extensions including among others advanced sensitivity analysis tools and the GAIA visual descriptive model. It thus provides decision makers with a much richer information at the expense of a more complex preference modeling. The SIR method is another interesting extension of PROMETHEE. On the other hand, AHP is quite different as it is designed to work with qualitative input data and it is based on a very specific pairwise comparison principle. Many people have been critical about the theoretical basis of AHP. Yet, it is one of the most widely used multicriteria decision aid methods. Finally, goal programming methods are based on the mathematical programming model. They are an appropriate choice when decisions are related to decision variables whose best values should be determined under a set of constraints.