At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.

Public corporations and private businesses operate in an increasingly complex, uncertain, and interconnected world. When evaluating investment decisions, business managers can no longer base their decisions primarily on expected financial return. They now must now consider a host of performance value measures (i.e., criteria) pertaining to issues such as environmental and social governance, sustainability, and stakeholder satisfaction. In addition, corporate managers must ensure that their investment decisions are aligned with the company’s vision, mission, and values in order to maintain investor confidence and protect brand image. Lastly, to be truly successful, business managers must assess the risks associated with each performance measure and manage their impacts during project implementation. This book takes a pragmatic business and economics view towards evaluating competing investment alternatives and/or capital project strategies. It provides a practical step-by- step process using a structured decision analysis framework to evaluate, understand, quantify, and measure project invesment strategies in light of multiple stakeholder objectives and success criteria. This process assists in helping stakeholders (internal and external) achieve a shared understanding of project issues and to facilitate convergence towards a mutually acceptable solution. The approach considers available choices, identified uncertainties, constraints, necessary tradeoffs, and preferences so as to identify solutions that maximize overall benefits while minimizing overall costs and risk. A real world case study is presented in the early chapters and the process steps are demonstrated through application to this case study. Recent advances in technology allow for investment strategies to be evaluated against multiple criteria within one integrated platform. This book guides the reader in performing multi-criteria decision analysis, including the use of Monte Carlo simulation, within an MS Excel environment using native MS Excel and as well as add-in programs such Palisades Decision Tools suite. Example model structures, screen shots, formulas, and output results are provided throughout the book using an illustrative case study.

First published in 1999, this volume consists of selected papers presented at the North American Meetings of the RSAI along with invited contributions from scholars active in the field of spatial multicriteria decision making and analysis. It is meant to present diverse lines of research in spatial multicriteria decision making and analysis under the multidisciplinary umbrella of Geographic Information Science. The first part explores selected theoretical and conceptual aspects of spatial multicriteria decision making and analysis not confined to any specific application domain. Part 2 consists of six chapters focusing on various forms of location decision and analysis problems. Finally, part 3 contains five chapters on various spatial decision problems whose systemic scope sets them apart from locational decision problems.

A guide to the various models and methods to multicriteria decision-making in conditions of uncertainty presented in a systematic approach Multicriteria Decision-Making under Conditions of Uncertainty presents approaches that help to answer the fundamental questions at the center of all decision-making problems: "What to do?" and "How to do it?" The book explores methods of representing and handling diverse manifestations of the uncertainty factor and a multicriteria nature of problems that can arise in system design, planning, operation, and control. The authors—noted experts on the topic—and their book covers essential questions, including notions and fundamental concepts of fuzzy sets, models and methods of multiobjective as well as multiattribute decision-making, the classical approach to dealing with uncertainty of information and its generalization for analyzing multicriteria problems in condition of uncertainty, and more. This comprehensive book contains information on "harmonious solutions" in multiobjective problem-solving (analyzing “i>X, F> models), construction and analysis of “i>X, R/i” models, results aimed at generating robust solutions in analyzing multicriteria problems under uncertainty, and more. In addition, the book includes illustrative examples of various applications, including real-world case studies related to the authors’ various industrial projects. This important resource: Explains the design and processing aspect of fuzzy sets, including construction of membership functions, fuzzy numbers, fuzzy relations, aggregation operations, and fuzzy sets transformations Describes models of multiobjective decision-making (“i>X. M/i” models), their analysis on the basis of using the Bellman-Zadeh approach to decision-making in a fuzzy environment, and their diverse applications, including multicriteria allocation of resources Investigates models of multiattribute decision-making (“i>X, R/i” models) and their analysis on the basis of the construction and processing of fuzzy preference relations as well as demonstrating their applications to solve diverse classes of multiattribute problems Explores notions of payoff matrices and fuzzy-set-based generalization and modification of the classic approach to decision-making under conditions of uncertainty to generate robust solutions in analyzing multicriteria problems Written for students, researchers and practitioners in disciplines in which decision-making is of paramount relevance, Multicriteria Decision-Making under Conditions of Uncertainty presents a systematic and current approach that encompasses a range of models and methods as well as new applications.

This collection of papers gives a broad overview of the state of the art in Multiple Criteria Decision Making (MCDM), in both theory and practice. Topical sections are ranging from preference modelling and methodological developments to a number of applications of MCDM thinking. Special sections are devoted to applications in natural resources and environmental management issues, to negotiation and group decision support, and to philosophical issues, particularly in the interface between systems thinking and MCDM. The book will be relevant not only to those working in the area of MCDM, but also to researchers and practitioners concerned with broader areas of management science, especially those concerned with decision support systems and negotiation support.

This volume is a collection of contributions to the subject of multicriteria decision making and differential games, all of which are based wholly or in part on papers that have appeared in the Journal of Optimization Theory and Applications. The authors take this opportunity to revise, update, or enlarge upon their earlier publications. The theory of multicriteria decision making and differential games is concerned with situations in which a single decision maker is faced with a multiplicity of usually incompatible criteria, performance indices or payoffs, or in which a number of decision makers, or players, must take into account criteria each of which depends on the decisions of all the decision makers. The first six chapters are devoted to situations involving a single decision maker, or a number of decision makers in complete collaboration and thus being in effect a single decision maker. Chapters I -IV treat various topics in the theory of domination structures and nondominated decisions. Chapter V presents a discussion of efficient, or Pareto-optimal, decisions. The approach to multicriteria decision making via preference relations is explored in Chapter VI. When there is more than one decision maker, cooperation, as well as noncooperation, is possible. Chapters VII and VIII deal with the topic of coalitions in a dynamic setting, while Chapters IX and X address the situation of two unequal decision makers, a leader and a follower.

The paper presents multicriteria decision making method with single value neutrosophic sets (SVNS), namely COPRAS-SVNS. The complex proportional assessment method (COPRAS) has shown accurate results for the solution of various multicriteria decision making problems in the engineering field.

In multicriteria decision making (MCDM), multi-hesitant fuzzy linguistic term sets (MHFLTSs) can eliminate the limitations of hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic sets (HFLSs), and emphasize the importance of a repeated linguistic term (LT). Meanwhile, there is usually an interrelation between criteria.

In this paper, we first introduce novel concepts of m-polar neutrosophic set (MPNS) and topological structure on m-polar neutrosophic set by combining the mpolar fuzzy set (MPFS) and neutrosophic set.

The paper presents the extension of VIKOR method for the solution of the multicriteria decision making problems, namely VIKOR-IVNS. The original VIKOR method was proposed for the solution of the decision problems with the conflicting and non-common measurable criteria. In this paper, a new extension of the crisp VIKOR method has been proposed.