Learning-based hyper-heuristics for combinatorial optimization select from among low-level operators or tune the parameters of a single metaheuristic. However, online selection among complete population-based metaheuristics that share one evolving population and its joint configuration through a common action space hav...
C. Carrasco, Broderick Crawford, Carlos Valle et al.· Biomimetics· 0 citations
Bio-inspiration has mainly been used to represent organisms, behaviors, or natural processes in the design of metaheuristics. This study proposes a different use: drawing on a biological phenomenon to model the temporal evolution of an internal parameter in an existing algorithm. Logarithmic Mean Optimization (LMO) is...
A chaotic discretization framework is presented that replaces the classical behavior of the two-step binarization technique to regulate the balance between exploration and exploitation and shows that the highest-performing chaotic mapping is heavily influenced by the specific landscape morphology evaluated.
Felipe Cisternas-Caneo, Broderick Crawford, Jorge Mendoza et al.· Biomimetics· 1 citation
Bio-inspired swarm metaheuristic algorithms constitute a widely used tool for solving complex optimization problems. However, the experimental characterization of their emergent behavior remains a methodological challenge. This study proposes an experimental framework for characterizing emergent behavior through swarm...
The Binary Hunger Games Search metaheuristic is selected because the relative quality of each individual determines its hunger level, which in turn regulates the movement of the population and the influence of the best solution found.
Broderick Crawford, Hugo Caballero, Gino Astorga et al.· Biomimetics· 0 citations
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