CIIC - Artigos em Revistas com Peer Review
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Browsing CIIC - Artigos em Revistas com Peer Review by Field of Science and Technology (FOS) "Ciências Naturais::Matemáticas"
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- Indicator-based multi objective evolutionary algorithms and an application in filament winding processPublication . Yevseyeva, Iryna; de Melo, Francisco Queirós; Grácio, José; Basto-Fernandes, VitorThis work presents recent developments on multi objective evolutionary algorithms, so-called set-based evolutionary algorithms. These techniques are shown to approximate a Pareto front of efficient solutions taking into account both quality of the approximation and its diversity, both important in the design of these methods. Set-based evolutionary algorithms outperform their predecessors on a variety of benchmark problems and are suggested as tools to be used for solving complex mechanical engineering problems, such as filament winding process discussed in this work.
- Solving large-scale SONET network design problems using bee-inspired algorithmsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelIn the past years, the number of users of Internet-based applications has exponentially increased and consequently the request for transmission capacity or bandwidth has significantly augmented. When managed properly, the ring networks are uniquely suited to deliver a large amount of bandwidth in a reliable and inexpensive way. In this paper, we consider two problems that arise in the design of optical telecommunication networks, namely the SONET Ring Assignment Problem (SRAP) and the Intraring Synchronous Optical Network Design Problem (IDP), known to be NP-hard. In SRAP, the objective is to minimise the number of rings (i.e., DXCs). In IDP, the objective is to minimise the number of ADMs. Both problems are subject to a ring capacity constraint. To solve these problems, we propose two bee-inspired algorithms: Hybrid Artificial Bee Colony and Hybrid Bees Algorithm. We hybridise the basic form of these algorithms with local search, in order to refine newly constructed solutions. We also perform comparisons with other algorithms from the literature and use larger instances. The simulation results verify the effectiveness and robustness of the proposed algorithms.
