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Nowadays, optimization has become an important issue for industrial systems and product development. From an engineering perspective, optimization implies adjusting or fine-tuning system designs considering one or more performance factors. Unfortunately, for many complex problems there is no optimization technique that can achieve the optimum solution in a reasonable computation time. As a result, the optimization process is often done manually. In recent years a myriad of optimization techniques have appeared, all inspired by phenomena observed in nature, such as behavioral patterns in animals (such as the exploration and search for food, moving, hunting, …), physical and chemical processes [1]. These techniques, often referred to as nature- or bio-inspired optimization algorithms, allow users to optimize a problem without requiring special knowledge about it: they only need to be informed about the fitness function to be optimized, and the mechanisms by which new candidate solutions can be produced. Each algorithm defines how existing solutions can be combined and modified to create new ones in an intelligent way to search for the best solution. Although they cannot guarantee that the optimum solution will be eventually achieved, they can automatically yield good solutions in reasonable computation times. These features make bio-inspired optimization proposals a promising research area and a great alternative to optimize complex processes, as has been already showcased in many real-world problems. In this work we present nature- and bio-inspired optimization from a global perspective. We describe techniques falling in this area, their evolution, how they operate, and why they bridge an important gap not covered by previous optimization techniques. On a critical note, we also give a clear view of the current situation in the area, indicating the positive aspects and issues that should be urgently improved. Considering this critical view, we suggest promising trends that we believe will lead us to a brighter future in nature- and bio-inspired optimization, plenty of successful examples of their application to real-world engineering problems. The manuscript is structured as follows: Section 2 describes bio-inspired optimization and exposes the reasons and advantages that make this area interesting from the scientific and practical points of view (focusing on introducing what they are and why they are useful). In Section 3 we examine the exciting panorama of recent applications in which nature- and bio-inspired optimization has become a central technology (the good), the upsurge of novel metaphors for the design of new proposals that do not lead to innovative solutions (the bad), and poor methodological practices that draw misleading conclusions that must be avoided in this field (the ugly). Finally, Section 4 summarizes the paper and highlights what is next to be done in the area of bio-inspired optimization (the hopeful), especially for engineering applications.

En el curso 2014-2015 se ha impartido por vez primera el “Máster en Ciencia de Datos e Ingeniería de Computadores” en la Universidad de Granada. Este máster surge de la unión de los anteriores “Máster en Soft Computing y Sistemas Inteligentes” y “Máster en Ingeniería de Computadores y Redes”, renovando completamente sus contenidos y ofreciendo una oportunidad de asociación entre varios grupos de investigación con un enorme potencial en el ámbito de las Tecnologías de la Información y de las Comunicaciones (TIC). Este máster proporciona al estudiante la oportunidad de formarse profesionalmente en campos con una gran demanda de personal cualificado y de enorme interés social, tales como el análisis de grandes cantidades de datos (big data) o el desarrollo de sistemas de propósito específico y plataformas de computación de altas prestaciones., The Master ’s Degree in Data Science and Computer Engineering has been taught at the University of Granada for the first time during academic year 2014-2015. This master comes from the combination of former masters in Soft Computing and Computer Engineering, but it completely renovates its contents and it provid es an opportunity for partnership and collaboration between several research groups with a great potential in the field of Information Technology and Communications (ICT). The proposed Master ’s Degree trains students as researchers in areas with a high demand for qualified staff and huge social interest, such as the analysis of large amounts of data (big data) or the development of embedded systems and platforms for high-performance computing., Universidad de Granada: Departamento de Arquitectura y Tecnología de Computadores; Vicerrectorado para la Garantía de la Calidad.