2022
Authors
Sequeiros, JA; Silva, R; Santos, AS; Bastos, J; Varela, MLR; Madureira, AM;
Publication
Lecture Notes in Mechanical Engineering
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. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
2022
Authors
Varela, L; Avila, P; Castro, H; Putnik, GD; Fonseca, LMC; Ferreira, L;
Publication
Sustainability (Switzerland)
Abstract
2022
Authors
Ribeiro, J; Tavares, J; Fontes, T;
Publication
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Intelligent Transport Systems
Abstract
2022
Authors
Tavares, J; Ribeiro, J; Fontes, T;
Publication
Transportation Research Procedia
Abstract
2022
Authors
Sousa, C; Teixeira, D; Carneiro, D; Nunes, D; Novais, P;
Publication
Integrated Computer-Aided Engineering
Abstract
2022
Authors
Pinheiro, S; Correia Simões, A; Pinto, A; Van Acker, BB; Bombeke, K; Romero, D; Vaz, M; Santos, J;
Publication
Studies in Systems, Decision and Control
Abstract
Objective: A systematic literature review was conducted to identify relevant ergonomic and safety factors for designing collaborative workspaces in industrial settings. Background: The growing use of smart and collaborative robots in manufacturing brings some challenges for the human-robot interaction design. Human-centered manufacturing solutions will improve physical and mental well-being, performance, productivity and sustainability. Method: A systematic review of the literature was performed based on the protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Results: After a search in the databases Scopus and Web of Science, applying inclusion and exclusion criteria, 33 publications in the English language, published between the years 2010 and 2020, remained in the final analysis. Publications were categorized in cognitive ergonomic factors (13), safety factors (10), physical ergonomic factors (6) and organizational ergonomic factors (4). The analysis of results reinforced that to optimize the design of collaborative workstations it is imperative to have a holistic perspective of collaboration, integrating multiple key factors from areas such as engineering, ergonomics, safety, sociology and psychological as well as manufacturing efficiency and productivity. Application: Considering the advantages of the use of cobots in manufacturing, the results of this review will be useful to support companies in implementing human-robot collaboration. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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