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The way citizens interact with cities affects overall life quality. Their participation in social decisions is of paramount importance for helping on public decisions that affect governance, regulation and education. This interaction has the potential of being boosted within the scope of smart and digital cities, especially by recent advances in blockchain technology. This work introduces insights about how smart cities' concepts and innovative technologies can help society to face daily challenges for improving citizens' awareness. Digital technologies are able to drive social and economic development by employing Information and Communication Technology (ICT) to promote innovation. In this context, e-governance, in conjunction with disruptive concepts such as blockchain, is showing up as a fundamental tool for a decentralized democracy. This study reviews, discusses, raises open points and presents suggestions towards an efficient, transparent and sustainable use of technology, applied to future cities. ; Thays A. Oliveira would like to thank the partnership with NeoResearch Community and support of Neo Foundation. Miquel Oliver was supported by the Spanish Government under projects TEC2016-79510-P (Proyectos Excelencia 2016); Miquel Oliver and Helena Ramalhinho were also supported by the 2017-SGR-1739 grant.

This paper focuses on iterated local search heuristics for the maximum cut‐clique (MCC, or clique neighborhood) problem. Given an undirected graph G = (V,E) and a clique C of G, the cut‐clique is the set of edges running between C and V\C, establishing the cut (C,V\C). The MCC in G is to find a clique with the largest number of edges in the neighborhood of the clique, also known as the maximum edge‐neighborhood clique. This problem has been recently introduced in the literature together with a number of applications, namely, in cell biology instances. However, it has only been addressed so far by exact methods. In this paper, we introduce the first approximate algorithms for tackling the MCC problem, compare the results with the exact methodologies, and explore a new application within marketing analysis, which provide a new alternative perspective for mining market basket problems. ; This work has been partially supported by the Portuguese National Funding by FCT (project PEst-OE/MAT/UI0152), Pedro Martins; and by the Ministerio de Economía y Competitividad (Spanish Government), A. Ladrón-de-Guevara (ECO2011-27942) and H. Ramalhinho (TRA2013-48180-C3-2-P).

This paper analyzes a realistic variant of the Permutation Flow-Shop Problem (PFSP) by considering a non-smooth objective function that takes into account not only the traditional makespan cost but also failure-risk costs due to uninterrupted operation of machines. After completing a literature review on the issue, the paper formulates an original mathematical model to describe this new PFSP variant. Then, a Biased-Randomized Iterated Local Search (BRILS) algorithm is proposed as an efficient solving approach. An oriented (biased) random behavior is introduced in the well-known NEH heuristic to generate an initial solution. From this initial solution, the algorithm is able to generate a large number of alternative good solutions without requiring a complex setting of parameters. The relative simplicity of our approach is particularly useful in the presence of non-smooth objective functions, for which exact optimization methods may fail to reach their full potential. The gains of considering failure-risk costs during the exploration of the solution space are analyzed throughout a series of computational experiments. To promote reproducibility, these experiments are based on a set of traditional benchmark instances. Moreover, the performance of the proposed algorithm is compared against other state-of-the-art metaheuristic approaches, which have been conveniently adapted to consider failure-risk costs during the solving process. The proposed BRILS approach can be easily extended to other combinatorial optimization problems with similar non-smooth objective functions. ; This research has been partially supported by the Spanish Ministry of Economy and Competitiveness, projects MTM2011-29064-C03-02, MTM2014-59179-C2-01 & TRA2013-48180-C3-P, and FEDER. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program.

This work focuses on internal logistics (IL), which is defined as the flows of materials inside the same business or the same plant. We centre on the IL activities of a car-assembling company. The main objective is to propose simulation models' concepts that evaluate assembling lines under the IL point of view. We present a real case study based on SEAT S.A., a company in the Volkswagen group. We developed a Discrete-Event Simulation model through the Plant Simulation software. The company set the main Key Performance Indicators, which are related to the logistics flows' performance (LFP) and an assembly lines' aisles utilisation. The results expose which aisles are overused, the disturbs among the logistics flows, and the LFP, regarding the total of backorders, the trips duration, and the routes' length in terms of distances and time. Moreover, we offer aset of best practices for further applications in that field. ; This work has been partially supported by the Industrial Ph.D. of Government of Catalonia (2016DI022) (Marcelus Fabri) and by the Government of Catalonia through the projects (2017-SGR-1739) (Helena Ramalhinho, Miquel Oliver).

Cities are constantly transforming and, consequently, attracting efforts from researchers and opportunities to the industry. New transportation systems are being built in order to meet sustainability and efficiency criteria, as well as being adapted to the current possibilities. Moreover, citizens are becoming aware about the power and possibilities provided by the current generation of autonomous devices. In this sense, this paper presents and discusses state-of-the-art transportation technologies and systems, highlighting the advances that the concepts of Internet of Things and Value are providing. Decentralized technologies, such as blockchain, are been extensively investigated by the industry, however, its widespread adoption in cities is still desirable. Aligned with operations research opportunities, this paper identifies different points in which cities' services could move to. This also study comments about different combinatorial optimization problems that might be useful and important for an efficient evolution of our cities. By considering different perspectives, didactic examples are presented with a main focus on motivating decision makers to balance citizens, investors and industry goals and wishes. ; Thays A. Oliveira, Vitor N. Coelho and Igor M. Coelho would like to thank the partnership with NeoResearch community and support of Neo Foundation. Miquel Oliver was supported by the Spanish Government under projects TEC2016-79510-P (Proyectos Excelencia 2016) and 2017-SGR-1739. Vitor N. Coelho was funded by FAPERJ grant number E-26/202.868/2016. Luiz S. Ochi, Fábio Protti and Igor M. Coelho were partially supported by the CNPq and FAPERJ. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.