J. A. López Gómez
In spite of technological advances, traffic problems continue to be a major concern in our society. The traffic models such as demand adjustment problem or network design problem, exhibit a bi-level structure, non-convexity, and non-differentiable features. In this context, some metaheuristic algorithms arise from the inspiration in nature and have been proven as an effective way to deal with these hard optimization problems. However, the main drawback of this strategy is its intensive computational cost. This work presents a hybridized Brain Storm Optimization (BSO) Algorithm, which is inspired into the brainstorming process which occur in human society to solve problems. The proposed method introduces in BSO a local search stage to accelerate and to improve the performance of the BSO.
Keywords: Brain Storm Optimization, Metaheuristics, Evolutionary Algorithms, Global Optimization
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WA2 Logistics and planning
June 1, 2016 9:00 AM
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