Abstract
Recent advances in high-throughput technologies have given rise to collecting large amounts of multidimensional heterogeneous data that provide diverse information on the same biological samples. Integrative analysis of such multisource datasets may reveal new biological insights into complex biological mechanisms and therefore remains an important research field in systems biology. Most of the modern integrative clustering approaches rely on independent analysis of each dataset and consensus clustering, probabilistic or statistical modeling, while flexible distance-based integrative clustering techniques are sparsely covered. We propose two distance-based integrative clustering frameworks based on bi-level and bi-objective extensions of the p-median problem. A hybrid branch-and-cut method is developed to find global optimal solutions to the bi-level p-median model. As to the bi-objective problem, an epsilon-constraint algorithm is proposed to generate an approximation to the Pareto optimal set. Every solution found by any of the frameworks corresponds to an integrative clustering. We present an application of our approaches to integrative analysis of NCI-60 human tumor cell lines characterized by gene expression and drug activity profiles. We demonstrate that the proposed mathematical optimization-based approaches outperform some state-of-the-art and traditional distance-based integrative and non-integrative clustering techniques.

Abstract
The Portuguese footwear industry registered a strong performance over the last few years and the openness to adopt new technologies was a key factor. Among these, the implementation of innovative logistic systems for the transport and assignment of work-in-process in manufacturing processes was a key technology. By means of case research it was analyzed an internal logistic system, deployed in a Portuguese large footwear producer, which reveals some weaknesses at the physical and cyber levels. A lack of managing applications was detected at the factory and enterprise levels, which contribute to lower levels of visibility of production and productivity. This article presents the development of a Cyber-Physical Production System, in the context of the Horizon 2020 research and innovation program BEinCPPS, that comprises four application experiments. These experiments were successful and the results demonstrated a relevant increase of production efficiency and decrease of maintenance costs.

Abstract
The implementation of efficient strategic decisions such as process design and capacity investment under uncertainty, during the product development process, is critical for the pharmaceutical industry. However, to tackle these problems the widely used multi-stage/scenario-based optimization formulations are still ineffective, especially for the first-stage (here-and-now) solutions where uncertainty has not yet been revealed. This study extends the authors' previous work addressing the stochastic product-launch planning problem, by developing a new Multi-Objective Integer Programming model, embedded in a unified decision-making framework, to obtain the final design strategy that "maximizes" productivity while considering the decision-maker preferences. An approximation of the efficient Pareto-front is determined, and a subsequent Pareto solutions analysis is made to guide the decision process. The developed approach clearly identifies the process designs and production capacities that "maximize" productivity as well as the most promising solutions region for investment. Moreover, a good balance between investment and capacity allocation was achieved.

Abstract
Metaheuristic Algorithms in Maritime Operations Optimization focuses on the seaside and port side problems regarding the maritime transportation. The book reviews and introduces the most important problems regarding the shipping network design, long-term and short-term scheduling and planning problems in both bulk and container shipping as well as liquid maritime transportation. Application of meta heuristic algorithm is important for these problems, as most of them are hard and time-consuming to be solved optimally.

Abstract
The widespread use of internet is changing the way supply chain echelons interact with each other in order to respond to increasing customer requests of personalized products and services. Companies acquainted with the concept of industry 4.0 (i4.0) embrace the use of internet to improve their internal and external processes, delivering the dynamic and flexible response customers want. This chapter aims to discuss how supply chains may benefit from the adoption of i4.0 technologies by their partners and highlights some of its implementation challenges. Eight technologies cover most of i4.0 applications: additive manufacturing; big data & analytics; cloud computing; cyber-physical systems; cyber security; internet of things; collaborative robotics; and visual computing. At individual level, technologies such as additive manufacturing, collaborative robots, visual computing and cyber-physical systems establish the connectivity of a certain company. However, the integration of the whole supply chain, based on the principles of i4.0, demands that information provided by each company (Big Data) is shared through a collaborative system based on Cloud Computing and Internet of Things technologies. To safely share useful information, Cyber Security techniques must be implemented in individual systems and cloud solutions. Summing up, even though the adoption of i4.0 demands an individual initiative, it will only raise the supply chain’s competitive advantage if all companies adapt their manufacturing and supply chain processes. The main advantage foreseen here is based on an improved communication system of the whole supply chain, bringing consumers closer to the production process. © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract
The purpose of this study is to investigate Second Generation Ethanol’s (SGE) production cycle in order to understand the level of SGE’s technological intensity in the integrated cycle. The suggested methodology comprises of a review of literature surrounding the requirements and indexes of technological intensity. A wide selection of database and review of specialized literature have been described to demonstrate the proposed discussion and conclusions. It has been observed that SGE puts forward a higher level of technological intensity in relation to First Generation Ethanol (FGE).