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Basic Aspects of the Multiple Criteria Decision Making Paradigm

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Designing Public Policies

Abstract

In this chapter we present the basic elements of the second analytical tool that we use in our research: multiple criteria decision making (MCDM). It stresses the aspects most related to the design of public policies. MCDM has been designed to overcome two of the key limitations of the traditional approach: (1) the difficulty of characterizing preferences by a single criterion and (2) the fact that rigid constraints are not always a realistic representation of feasibility for decision makers. We start by introducing some basic concepts underlying the MCDM methodology, as well as a general distance function that provides a unifying framework for all the MCDM techniques that will be used in the book. The chapter focuses on continuous MCDM techniques, starting with the generation of efficient solutions by multiobjective programming. Then we introduce compromise programming, which aims at providing solutions with a minimal distance from the ideal point. The third approach is goal programming, which is based on a Simonian satisficing logic rather than on a conventional optimization logic. We also discuss the advantages and disadvantages of different MCDM approaches within a policy making context and give a brief historical overview of MCDM.

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Notes

  1. 1.

    The term “Young Turks” usually refers to a group of young intellectuals, including John Maynard Keynes. They were graduate students at King’s College, Cambridge, who in the early twentieth century led a protest movement aiming to change the Victorian norms ruling the King´s.

References

  • André FJ, Romero C (2008) Computing compromise solutions: on the connections between compromise programming and composite programming. Appl Math Comput 195:1–10

    Article  Google Scholar 

  • Ballestero E, Romero C (1991) A theorem connecting utility function optimization and compromise programming. Oper Res Lett 10:421–427

    Article  Google Scholar 

  • Blasco F, Cuchillo-Ibáñez E, Morón MA, Romero C (1999) On the monotonicity of the compromise set in multicriteria problems. J Optim Theory Appl 102:69–82

    Article  Google Scholar 

  • Caballero R, Romero C (2006) Decisión Multicriterio: Un ejemplo de revolución científica Kuhniana. Boletín de la Sociedad Estadística e Investigación Operativa 22:9–15

    Google Scholar 

  • Caballero R, Rey L, Ruiz F (1996) Determination of satisfying and efficient solutions in convex multi-objective programming. Optimization 37:125–137

    Article  Google Scholar 

  • Charnes A, Cooper WW (1961) Management models and industrial applications of linear programming. Wiley, New York

    Google Scholar 

  • Charnes A, Cooper WW (1977) Goal programming and multiple objective optimization-Part I. Eur J Oper Res 1:39–54

    Article  Google Scholar 

  • Charnes A, Cooper WW, Ferguson R (1955) Optimal estimation of executive compensation by linear programming. Manage Sci 1:138–151

    Article  Google Scholar 

  • Cochrane JL, Zeleny M (eds) (1973) Multiple criteria decision making. University of South Carolina Press, Columbia

    Google Scholar 

  • Cohon JL (1978) Multiobjective programming and planning. Academic, New York

    Google Scholar 

  • Debreu G (1959) Theory of value-an axiomatic analysis of economic equilibrium. Wiley, New York

    Google Scholar 

  • Ehrgott M, Gandibleux X (eds) (2002) Multiple criteria optimization: state of the art annotated bibliographic survey. In: Kluwer's international series in operations research and management science, vol 52. Kluwer Academic, Boston

    Google Scholar 

  • Evans JP, Steuer RE (1973) A revised simplex method for linear multiple objective programming. Math Progr 5:54–72

    Article  Google Scholar 

  • Hannan EL (1980) Nondominance in goal programming, INFOR. Can J Oper Res Inform Process 18:300–309

    Google Scholar 

  • Ignizio JP (1976) Goal programming and extensions. Lexington Books, Massachusetts

    Google Scholar 

  • Ignizio JP (1983) Generalized goal programming. An overview. Comput Oper Res 10:277–289

    Article  Google Scholar 

  • Ignizio JP, Perlis JH (1979) Sequential linear goal programming. Comput Oper Res 6:141–145

    Article  Google Scholar 

  • Ijiri Y (1965) Management models and accounting for control. North-Holland, Amsterdam

    Google Scholar 

  • Koopmans TC (1951) Analysis of production as an efficient combination of activities. In: Koopmans TC (ed) Activity analysis of production and allocation. Wiley, New York

    Google Scholar 

  • Kuhn HW, Tucker AW (1951) Nonlinear programming. In: Neyman J (ed) Proceedings of the second berkeley symposium on mathematical statistics and probability. University of California Press, Berkeley

    Google Scholar 

  • Lee SM (1972) Goal programming for decision analysis. Auerbach, Philadelphia

    Google Scholar 

  • Marglin JA (1967) Public investment criteria. The Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  • Masud AS, Hwang CL (1981) Interactive sequential goal programming. J Oper Res Soc 32:391–400

    Google Scholar 

  • Romero C (1985) Multiobjective and goal programming approaches as a distance function model. J Oper Res Soc 36:249–251

    Google Scholar 

  • Romero C (1991) Handbook of critical issues in goal programming. Pergamon, Oxford

    Google Scholar 

  • Romero C (2001) Extended lexicographic goal programming: a unifying approach. Omega Int J Manage Sci 29:63–71

    Article  Google Scholar 

  • Romero C (2004) A general structure of achievement function for a goal programming model. Eur J Oper Res 153:675–686

    Article  Google Scholar 

  • Simon HA (1956) Rational choice and the structure of the environment. Psychol Rev 63:129–138

    Article  Google Scholar 

  • Steuer RE (1994) Random problem generation and the computation of efficient extreme points in multiple objective linear programming. Comput Optim Appl 3:333–347

    Article  Google Scholar 

  • Steuer RE (1995) Manual for the ADBASE multiple objective linear programming package. University of Georgia, Athens

    Google Scholar 

  • Steuer RE, Gardiner LR, Gray J (1996) A bibliographic survey of the activities and international nature of multiple criteria decision making. J Multicrit Decis Anal 5:195–217

    Article  Google Scholar 

  • Tamiz M, Jones DF (1996) Goal programming and Pareto efficiency. J Inform Optim Sci 17:291–307

    Google Scholar 

  • Tamiz M, Jones DF, Romero C (1998) Goal programming for decision making: an overview of the current state-of-the-art. Eur J Oper Res 111:569–581

    Article  Google Scholar 

  • Tamiz M, Mirrazavi SK, Jones DF (1999) Extensions of pareto efficiency analysis to integer goal programming. Omega Int J Manage Sci 27:179–188

    Article  Google Scholar 

  • Yu PL (1973) A class of solutions for group decision problems. Manage Sci 19:936–946

    Article  Google Scholar 

  • Yu PL (1985) Multiple criteria decision making: concepts, techniques and extensions. Plenum, New York

    Book  Google Scholar 

  • Zadeh LA (1963) Optimality and non-scalar-valued performance criteria. IEEE Trans Autom Control AC-8:59–60

    Google Scholar 

  • Zeleny M (1973) Compromise programming. In: Cochrane JL, Zeleny M (eds) Multiple criteria decision making. University of South Carolina Press, Columbia

    Google Scholar 

  • Zeleny M (1974) A concept of compromise solutions and the method of the displaced ideal. Comput Oper Res 1:479–496

    Article  Google Scholar 

  • Zeleny M (1982) Multiple criteria decision making. McGraw-Hill, New York

    Google Scholar 

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Correspondence to Francisco J. André .

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André, F.J., Cardenete, M.A., Romero, C. (2010). Basic Aspects of the Multiple Criteria Decision Making Paradigm. In: Designing Public Policies. Lecture Notes in Economics and Mathematical Systems, vol 642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12183-8_3

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  • DOI: https://doi.org/10.1007/978-3-642-12183-8_3

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