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Integrating Soft Computing into Strategic Prospective Methods pp 43–66Cite as

Fuzzy Optimization and Reasoning Approaches

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 387))

Abstract

Long-term strategic reflection is a process that faces several challenges. Among them the uncertainty, which may be due to a multitude of reasons. The literature covers a wide range of contributions with methods and models focused on dealing with uncertainty in terms of optimization of complex systems and little on dealing with conjecture processes to build knowledge about the future. The Future Studies and Soft Computing fields offer a meeting place for the notions of experience, meta-knowledge, macro-effects and non-arbitrariness. This chapter develops a proposed link between the two fields to help decision makers change their ways of thinking, make new decisions about the choices they have to make and learn to plant new seeds of the future.

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Notes

  1. 1.

    Meaning the so-called Possibilistic Relational Universal Fuzzy (PRUF).

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Authors and Affiliations

  1. School of Management, Universidad Externado de Colombia, Bogotá, Colombia

    Raúl Trujillo-Cabezas

  2. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    José Luis Verdegay

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  1. Raúl Trujillo-Cabezas
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  2. José Luis Verdegay
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Correspondence to Raúl Trujillo-Cabezas .

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Trujillo-Cabezas, R., Verdegay, J.L. (2020). Fuzzy Optimization and Reasoning Approaches. In: Integrating Soft Computing into Strategic Prospective Methods. Studies in Fuzziness and Soft Computing, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-030-25432-2_3

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