Multiple Criteria Decision Making by Multiobjective Optimization

1. Front Matter

   Pages i-xxii

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2. Introduction

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 1-13

3. Solving Decision Problems

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 15-18

4. Decision Problem: Selection of a Single Variant

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 19-23

5. Derivation of Efficient Variants

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 25-35

6. Decision Problem: Selection of a Variant Portfolio—The Discrete Case

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 37-42

7. Decision Problem: Selection of a Variant Portfolio—The Continuous Case

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 43-49

8. Derivation of Efficient Portfolios

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 51-59

9. Supporting the Process of the Most Preferred Variant Selection

   • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

   Pages 61-71

10. Decision Problems, Continuation

    • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

    Pages 73-96

11. Decision Problem: Selection of a Stock Portfolio

    • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

    Pages 97-102

12. Relations

    • Ignacy Kaliszewski, Janusz Miroforidis, Dmitry Podkopaev

    Pages 103-109

13. Back Matter

    Pages 111-118

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This textbook approaches optimization from a multi-aspect, multi-criteria perspective. By using a Multiple Criteria Decision Making (MCDM) approach, it avoids the limits and oversimplifications that can come with optimization models with one criterion. The book is presented in a concise form, addressing how to solve decision problems in sequences of intelligence, modelling, choice and review phases, often iterated, to identify the most preferred decision variant. The approach taken is human-centric, with the user taking the final decision is a sole and sovereign actor in the decision making process. To ensure generality, no assumption about the Decision Maker preferences or behavior is made. The presentation of these concepts is illustrated by numerous examples, figures, and problems to be solved with the help of downloadable spreadsheets. This electronic companion contains models of problems to be solved built in Excel spreadsheet files.

Optimization models are too often oversimplifications of decision problems met in practice. For instance, modeling company performance by an optimization model in which the criterion function is short-term profit to be maximized, does not fully reflect the essence of business management. The company’s managing staff is accountable not only for operational decisions, but also for actions which shall result in the company ability to generate a decent profit in the future. This calls for management decisions and actions which ensure short-term profitability, but also maintaining long-term relations with clients, introducing innovative products, financing long-term investments, etc. Each of those additional, though indispensable actions and their effects can be modeled separately, case by case, by an optimization model with a criterion function adequately selected. However, in each case the same set of constraints represents the range of company admissible actions. The aim and the scope of this textbook is to present methodologies and methods enabling modeling of such actions jointly.

• Multiple Criteria Decision Making
• Multicriteria Optimization
• Pareto Optimality
• Multi Aspect Decision Environment
• Variant Portfolio Selection
• Decision Making
• MCDM
• Multiobjective Optimization

• Systems Research Institute, Polish Academy of Sciences Systems Research Institute, Warszawa, Poland

  Ignacy Kaliszewski, Dmitry Podkopaev

• Systems Research Institute, Polish Academy of Sciences Systems Research Institute, Wrocław, Poland

  Janusz Miroforidis

Ignacy Kaliszewski, Full Professor at the Systems Research Institute of the Polish Academy of Sciences, graduated from the Technical University of Warsaw. He got his Ph.D. and habilitation degrees from the Systems Research Institute of the Polish Academy of Science for his research in quantitative management science and operations research. He has published over 40 scientific papers in journals and books of international circulation and two monographs: Quantitative Pareto Analysis by Cone Separation Technique (Kluwer Academic Publ., Dordrecht, 1994), Soft Computing for Complex Multiple Criteria Decision Making (Springer, 2006). His current field of research is decision making in multicriteria environment.

Janusz Miroforidis is an Assistant Professor at the Systems Research Institute of the Polish Academy of Sciences. He received his M.S. degree in computer science from the University of Wrocław, and his Ph.D. from the Systems Research Institute of the Polish Academy of Science for his research in soft computing and MCDM methods for management needs. His major research interests include computer aided multiple criteria decision making, particularly as applied to complex decision problems and evolutionary multiobjective optimization. He is a co-founder of Treeffect, a consulting company.

Dmitry Podkopaev  is a Researcher and Associate Professor for the Systems Research Institute at the Polish Academy of Sciences. His interests include Multiple Criteria Decision Making and Discrete Optimization. He has experience in research and software development projects (as Analyst, Developer, Programmer), as well as high school teaching.

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