Javier H. López

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Particle Swarm Optimization (PSO) is a metaheuristic that is highly used to solve monoand multi-objective optimization problems. Two well-differentiated PSO versions have been defined – one that operates in a continuous solution space and one for binary spaces. In this paper, a new version of the Binary PSO algorithm is presented. This version improves its(More)
In this paper, the use of evolutionary metaheuristics for the optimization of emergency medical services (EMS) applied to a real-world case in Argentina is analyzed. The problem requires the simultaneous optimization of two opposing objectives -- reducing service delay time and minimizing the use of third-party medical vehicle. Therefore, a multiobjective(More)
Disclosing interactions between pesticides and bee infections is of most interest to understand challenges that pollinators are facing and to which extent bee health is compromised. Here, we address the individual and combined effect that three different pesticides (dimethoate, clothianidin and fluvalinate) and an American foulbrood (AFB) infection have on(More)
Particle Swarm Optimization (PSO) is a metaheuristic that has been successfully applied to linear and non-linear optimization problems in functions with discrete and continuous domains. This paper presents a new variation of this algorithm - called oscPSO - that improves the inherent search capacity of the original (canonical) version of the PSO algorithm.(More)
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