Browsing by Keyword "Differential Evolution"
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Item Hybridizing differential evolution and novelty search for multimodal optimization problems(Association for Computing Machinery, Inc, 2019-07-13) Martinez, Aritz D.; Fister, Iztok; Osaba, Eneko; Fister, Iztok; Oregi, Izaskun; Ser, Javier Del; IA; QuantumMultimodal optimization has shown to be a complex paradigm underneath real-world problems arising in many practical applications, with particular prevalence in physics-related domains. Among them, a plethora of cases within the computational design of aerospace structures can be modeled as a multimodal optimization problem, such as aerodynamic optimization or airfoils and wings. This work aims at presenting a new research direction towards efficiently tackling this kind of optimization problems, which pursues the discovery of the multiple (at least locally optimal) solutions of a given optimization problem. Specifically, we propose to exploit the concept behind the so-called Novelty Search mechanism and embed it into the self-adaptive Differential Evolution algorithm so as to gain an increased level of controlled diversity during the search process. We assess the performance of the proposed solver over the well-known CEC'2013 suite of multimodal test functions. The obtained outcomes of the designed experimentation supports our claim that Novelty Search is a promising approach for heuristically addressed multimodal problems.Item Resource allocation in rate-limited OFDMA Systems: A hybrid heuristic approach(2011) Del Ser, Javier; Bilbao, Miren Nekane; Gil-Lopez, Sergio; Matinmikko, Marja; Salcedo-Sanz, Sancho; IAThis paper presents a novel resource allocation procedure for OFDMA downlinks, which stems from an hybridization of the Harmony Search and the Differential Evolution heuristic algorithms. In this setup it is known that optimum subcarrier and power allocation is achieved through 1) assigning each subcarrier to the user with highest channel gain at the given frequency, and 2) a Water-Filling procedure over the set of considered channel gains. This work addresses the scenario where stringent rate constraints are imposed for each user at the transmitter, scenario where the previous optimum resource allocation procedure no longer holds. The proposed iterative technique hinges on the aforementioned combinatorial heuristics, jointly with an iterative greedy subcarrier shifting procedure that accounts for the fulfillment of the established rate restrictions. Preliminary simulation results are provided for the extended vehicular ITU channel model, which shed light on the performance of the proposed allocation procedure.