Abstract
There are Optimization Problems that are too complex to be solved efficiently by deterministic methods. For these problems, where deterministic methods have proven to be inefficient, if not completely unusable, it is common to use approximate methods, that is, optimization methods that solve the problems quickly, regardless of their size or complexity, even if they do not guarantee optimal solutions. In other words, methods that find acceptable solutions, efficiently. One particular type of approximate method, which is particularly effective in complex problems, are metaheuristics. Particle Swarm Optimization is a population-based metaheuristic, which has been particularly successful. In order to broaden the application and overcome the limitation of Particle Swarm Optimization, a discrete version of the metaheuristics is proposed. The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some promising results.

Abstract
In this paper, a decision support application, for the air cargo planning and distribution, is proposed. The freight forwarding sector has been working to be assertive and efficient in responding to the market through an efficient approach to planning and allocation problems. The main goal is to minimize costs and improve performance. A real air cargo distribution problem for a freight forwarder was addressed. This project emerged from the need to efficiently plan and minimize costs for the distribution of thousands of m(3) (cubic meters) of air cargo, while considering the market restrictions, such as aircraft availability and transportation fees. Through the GRG algorithm adaptation to the real problem, it was possible to respond to the main goal of this paper. The development of an easy-to-use application ensures a quick response in the air distribution planning, focusing on cost reduction in transportation. With the application development it is possible to obtain real earnings with immediate effect.

Abstract
The present study consists in the comparison of two metaheuristics in a scheduling problem (SP), in particular in the minimization of the makespan in flowshop problem. The two selected metaheuristics were DABC (Discrete Artificial Bee Colony) and ACO (Ant Colony Optimization). For the performance analysis, the metaheuristics were tuned with an extensive DOE study, subsequently, several tests were performed. Thirty-one evenly distributed instances were generated for a in-depth analysis and each one was subjected to three runs for each metaheuristic. Through the results obtained, it was possible to concluded that the DABC has a better performance when compared to SA and ACO. SA and ACO have a similar performance in the chosen problem. These conclusions were supported by descriptive statistics and statistical inference. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
In the context of the COVID-19 pandemic, public spaces had to be quickly adapted to the new circumstances especially under the uncertainty of the pandemic development. Door handles are some of the most touched surfaces and so, this point of contagion was chosen to be tackled and two solutions were developed that would prevent direct touch with the handle: a portable and a fixed device. The portable device (HYHOOK + HYTIP) is a hook-like device holding a finger cover, which permits to open doors and push buttons safely. The fixed device (HANDGENIC) is meant to be assembled in door handles to equip buildings, such as universities or schools. With the fixed device, the user can open the door using their forearm which makes them less likely to transfer any particles to eyes, nose or mouth. The 3D printing Fused Filament Fabrication (FFF) process was selected as manufacturing technique, which allows the fast production of prototypes. This work portrays the development process and design iterations taking into consideration the concerns about the functioning of the devices and possible failures or alternative uses. To assure structural integrity of the parts, finite element (FE) analysis was used to verify its mechanical response. As conclusion, it was found that FE analysis indicate that the devices are structurally sound to be used in public spaces and that 3D printing is a useful way to rapidly develop devices while testing several design possibilities.

Abstract
As the availability of computational power and communication technologies increases, Humans and systems are able to tackle increasingly challenging decision problems. Taking decisions over incomplete visions of a situation is particularly challenging and calls for a set of intertwined skills that must be put into place under a clear rationale. This work addresses how to deliver autonomous decisions for the management of a public street lighting network, to optimize energy consumption without compromising light quality patterns. Our approach is grounded in an holistic methodology, combining semantic and Artificial Intelligence principles to define methods and artefacts for supporting decisions to be taken in the context of an incomplete domain. That is, a domain with absence of data and of explicit domain assertions.

Abstract
The process of digital transformation is based on horizontal and vertical strategies, along with models and technologies used to share information and analyse data that supports decision making. In this context, sharing information securely and intelligibly using standardized architectures is crucial for the digital transformation journey of the companies. This article describes the International Data Spaces as a disruptive model for sharing information inside a network. This work will be evaluated within marketplaces platforms scope. © 2022 The Author(s).