Intelligent Techniques for R & D Project Selection in Large Social Organizations

 

Técnicas Inteligentes para la Selección de Proyectos de I & D en las Grandes Organizaciones Públicas

 

Eduardo Fernandez¹, Fernando Lopez², Jorge Navarro³ and Alfonso Duarte⁴

 

¹ Universidad Autónoma de Sinaloa e–mail eddyf@uas.uasnet.mx

² Universidad Autónoma de Nuevo León e–mail ferny_65@yahoo.com

³ Centro de Ciencias de Sinaloa e–mail navarro@computo.ccs.net.mx

⁴ Estudiante de Maestría, Universidad Autónoma de Sinaloa e–mail alfonsoduarte@gmail.com

 

Article received on March 22, 2004
Accepted on January 13, 2006

 

Abstract

Funding R&D projects is perhaps the most important task faced by large public organizations, in charge of promoting science and technology in different countries. However, most popular ways to solve this decision problem are based on too simple decision models and weak heuristics. In this paper a new methodology is presented to assist top level managers of those organizations during the project evaluation phase until the final decision. This methodology covers the following central points: a)a measure of the global impact and probability of success as main attributes to access the quality of a R&D project; b) a way to represent the knowledge, preferences and beliefs from the top level managers, and an approach to take into account that information in the evaluation process ; c) a way to update the beliefs of the top level managers by taking into account the experience of the whole organization; d)  a numerical model of the quality of a project portfolio that can be used for improving final portfolios; e) an evolutionary algorithm to explore the set of portfolios searching for the very good solutions. We also discuss the functional structure of a software application which implements the proposed methods. In some examples of real size our proposal clearly outperforms traditional methods.

Keywords: Project management, decision tables, evolutionary algorithms, decision support systems.

 

Resumen

La selección de buenos proyectos es quizás el problema crucial que enfrentan las grandes organizaciones públicas encargadas de promover la ciencia y la tecnología. Sin embargo, a pesar de los avances tecnológicos para el procesamiento de información, la selección de proyectos de I&D en las convocatorias que se llevan a cabo en muchos países se sigue basando en modelos de evaluación y decisión demasiado simples, pobres desde el punto de vista del estado del arte de la ciencia de la administración y de la modelación matemático–computacional. En este trabajo se presenta un nuevo procedimiento cuyo núcleo se compone de a) medición de impacto y probabilidad de éxito como atributos esenciales de calidad de un proyecto de I&D; b) una forma de representar el conocimiento, preferencias y creencias de la alta dirección de la organización, y un método para reflejar esta información en el proceso de evaluación; c) un modo de actualizar las creencias de esa alta dirección utilizando la experiencia de la propia organización; d) un modelo numérico de la calidad de la cartera de proyectos, susceptible de ser optimizado, y e)  un algoritmo evolutivo para explorar el conjunto de carteras en busca de las mejores soluciones. Se discute también la estructura funcional de un sistema que implementa el conjunto de métodos propuestos. En ejemplos de tamaño real la propuesta logra soluciones mucho mejores que las tradicionales.

Palabras claves: gestión de proyectos, algoritmos evolutivos, modelos de decisión, sistemas inteligentes de apoyo a la decisión.

 

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Acknowledgements

Authors gratefully acknowledge the support from the Mexican National Council for Science and Technology (CONACYT) and the Autonomous University of Sinaloa.

 

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Appendix 1. A Method for Group Sorting

We have developed a new method for group evaluation different from traditional approaches based on voting or average values. The main reason for choosing a more complicated way comes from the fact that a compensatory scheme or a majority rule are not always well suited for group decision–making. In these decision processes, veto effects are often very important to be ignored. The proposed method works with the natural heuristic used by collaborative groups for making reasonable or consensus agreements, based on universally accepted majority rules combined with the necessary observance of significative minorities, principles of fairness and equity. The ELECTRE's ideas of concordance and discordance are in the basis of this approach, which can be summarized as follows:

Let E be a scale used for group evaluation. Each group member expresses his/her opinion using stages of E.

1.a To measure the strength of the arguments in favor to the proposition PG " s is collectively preferred to s'". The power of the concordance coalition is modeled by a concordance index, which depends on the number of group members supporting PG .

1.b To measure the strength of the arguments against PG. The power of discordance coalition is modeled by a veto function, which depends on the number of group members in strong disagreement with PG.

1.c To combine the previous measures for defining a degree of truth σG (s,s') associated to PG.

To use σG for deriving a preference ranking of the levels . The first ranked level s* is identified as the group choice.

A deep discussion and a favorable comparison of this proposal to Borda's and Condorcet's methods can be found in (Fernandez and Olmedo, 2005, 2006).