Multiple Criteria Decision Analysis (MCDA) 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, MCDA 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 about MCDA (all in the ISOR series), and it brings all the latest advancements into focus. Looking at developments in the applications, methodologies and foundations of MCDA, 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 MCDA in Changeable Spaces, Stochastic Multicriteria Acceptability Analysis, Robust Ordinal Regression, and many more challenging issues.

Editors are three of the most prominent researchers in the field Prestigious group of contributors Addresses development in foundation, methodologies, and newest applications Includes supplementary material: sn.pub/extras

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