Jin-Kao Hao

Matthias Ehrgott

Carlos M. Fonseca

Xavier Gandibleux

Marc Sevaux

Multi-criterionoptimizationreferstooptimizationproblemswithtwoormore- jectives expressing con?icting goals that are formulated within a mathematical programming framework. The problems addressed may involve linear or nonl- ear objective functions and/or constraints, continuous or discrete variables, and may or may not be a?ected by uncertainty in the data. This branch of multiple criteria decision making (MCDM) ?nds application in numerous domains: en- neering design, health, transportation,telecommunications, bioinformatics, etc. The concept of a unique optimal solution does not apply as soon as multiple objectives are optimized simultaneously. The models and methods introduced in multi-criterion optimization deal with the concept of a set of e?cient (also called Pareto optimal) solutions. E?cient solutions imply trade-o?s between the di?erentcriteria. Thecomputationofthee?cientsolutionsetmaybehardwhen the size of the problem is large, when the problem is computationally complex, when the data are not crisp. It is then often impossible to guarantee the com- tation of exact solutions. In that case, approximate solutions, i. e. , sub-optimal solutionscomputedwithlimitedandcontrolledresources,suchasavailabletime, are of interest. This is the domain of multi-objective metaheuristics, of which evolutionary multi-criterion optimization (EMO) is de?nitely the most pro- nent representative. The success of EMO is due to the simplicity of its concepts and the generality of its methods, and is clearly expressed by the many impr- sive success stories reported in the literature. Research activities in EMO have boomed since the mid-1990s. Three g- erations of work are identi?able throughout the years.

5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009, Proceedings

Evolutionary Multi-Criterion Optimization

Theodor Stewart

Jyrki Wallenius

Boris Naujoks

In the twenty-first century the sustainability of energy and transportation systems is on the top of the political agenda in many countries around the world. Environmental impacts of human economic activity necessitate the consideration of conflicting goals in decision making processes to develop sustainable systems. Any sustainable development has to reconcile conflicting economic and environmental objectives and criteria. The science of multiple criteria decision making has a lot to offer in addressing this need. Decision making with multiple (conflicting) criteria is the topic of research that is at the heart of the International Society of Multiple Criteria Decision Making. This book is based on selected papers presented at the societies 19th International Conference, held at The University of Auckland, New Zealand, from 7th to 12th January 2008 under the theme "MCDM for Sustainable Energy and Transportation Systems''.

Proceedings of the 19th International Conference on Multiple Criteria Decision Making, Auckland, New Zealand, 7th - 12th January 2008

Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems

Salvatore Greco

José Rui Figueira

Multiple Criteria Decision Making (MCDM) is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management planning process. A key area of research in OR/MS, MCDM is now being applied in many new areas, including GIS systems, AI, and group decision making. This volume is in effect the third in a series of Springer books by these editors (all in the ISOR series), and it brings all the latest developments in MCDM into focus. Looking at developments in the applications, methodologies and foundations of MCDM, it presents research from leaders in the field on such topics as Problem Structuring Methodologies; Measurement Theory and MCDA; Recent Developments in Evolutionary Multiobjective Optimization; Habitual Domains and Dynamic MCDM in Changeable Spaces; Stochastic Multicriteria Acceptability Analysis; and many more chapters.

Trends in Multiple Criteria Decision Analysis

Multiobjective Discrete and Combinatorial Optimization

In two volumes, this new edition presents the state of the art in Multiple Criteria Decision Analysis (MCDA). Reflecting the explosive growth in the field seen during the last several years, the editors not only present surveys of the foundations of MCDA, but look as well at many new areas and new applications. Individual chapter authors are among the most prestigious names in MCDA research, and combined their chapters bring the field completely up to date. Part I of the book considers the history and current state of MCDA, with surveys that cover the early history of MCDA and an overview that discusses the “pre-theoretical” assumptions of MCDA. Part II then presents the foundations of MCDA, with individual chapters that provide a very exhaustive review of preference modeling, along with a chapter devoted to the axiomatic basis of the different models that multiple criteria preferences. Part III looks at outranking methods, with three chapters that consider the ELECTRE methods, PROMETHEE methods, and a look at the rich literature of other outranking methods. Part IV, on Multiattribute Utility and Value Theories (MAUT), presents chapters on the fundamentals of this approach, the very well known UTA methods, the Analytic Hierarchy Process (AHP) and its more recent extension, the Analytic Network Process (ANP), as well as a chapter on MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). Part V looks at Non-Classical MCDA Approaches, with chapters on risk and uncertainty in MCDA, the decision rule approach to MCDA, the fuzzy integral approach, the verbal decision methods, and a tentative assessment of the role of fuzzy sets in decision analysis. Part VI, on Multiobjective Optimization, contains chapters on recent developments of vector and set optimization, the state of the art in continuous multiobjective programming, multiobjective combinatorial optimization, fuzzy multicriteria optimization, a review of the field of goal programming, interactive methods for solving multiobjective optimization problems, and relationships between MCDA and evolutionary multiobjective optimization (EMO). Part VII, on Applications, selects some of the most significant areas, including contributions of MCDA in finance, energy planning problems, telecommunication network planning and design, sustainable development, and portfolio analysis. Finally, Part VIII, on MCDM software, presents well known MCDA software packages.

State of the Art Surveys

Multiple Criteria Decision Analysis

José Figueira

MULTIPLE CRITERIA DECISION ANALYSIS: State of the Art Surveys is the most comprehensive work available to survey the state of the art in MCDA to date. Its 25 chapters are organized in eight parts and are written by 52 international leading experts. Each of these parts covers one of the central streams of multiple criteria decision analysis literature. These literature streams are: MCDA today, Foundations of MCDA, Our Ranking Methods, Multiattribute Utility Theory, Non-Classical MCDA Approaches, Multiobjective Mathematical Programming, Applications, and MCDM Software. The handbook presents the most up-to-date discussions on well-established methodologies and theories in the field, while systematically surveying emerging fields in MCDA such as conjoint measurement, fuzzy preferences, fuzzy integrals, rough sets, etc. MULTIPLE CRITERIA DECISION ANALYSIS: State of the Art Surveys is a valuable reference volume (more than 2000 references) for the field of decision analysis. It provides graduate students, researchers, and practitioners with a sweeping survey of MCDA theory, methodologies, and applications. It is a handbook that is particularly suitable for use in seminars in Decision Analysis, Decision Support, and Decision Theory.

Multiple Criteria Decision Analysis: State of the Art Surveys

Matthias Ehrgott

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