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.
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.
1 February 2017 in Computers & Operations Research
This paper presents an Evolution Strategy (ES) based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration-exploitation balance. To validate the proposal, this framework is applied to solve three different NP-Hard combinatorial optimization problems: Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks; Unrelated Parallel Machine Scheduling Problem with Setup Times; and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results pointed out the convergence of the proposed model and hi...
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