Genetic-Algorithms-Based Approach for Bilevel Programming Models

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Traffic signal timing optimisation based on genetic algorithm approach, including drivers’ routing (2004, methodology): “Genetic Algorithms (GAs), first introduced by Goldberg (1989), have been applied to solve the ENDP (Lee and Machemehl, 1998; Cree et al., 1999; Yin, 2000).”
Sustainability SI: Optimal Prices of Electricity at Public Charging Stations for Plug-in Electric Vehicles (2016, methodology): “…algorithm, a pattern search method guided by simplex derivatives, to solve the bi-level model (Custódio and Vicente 2007; Custódio et al. 2010), after reviewing and comparing a variety of derivative-free algorithms including metaheuristics (e.g., Yin 2000; Kolda et al. 2003; More and Wild 2009).”
A bilevel optimization approach to automated parameter tuning (2014, methodology): “For instance, in [28, 45, 26] the upper level optimization task is handled using an evolutionary algorithm and the lower level is handled using a classical approach.”
A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications (2017, background): “One of the first studies, utilizing an evolutionary approach for multiobjective bilevel optimization was by Yin [187].”
Stochastic Transportation Network Design Problem with Spatial Equity Constraint (2004, methodology): “The binary representation has been used in GA to solve NDP (15).”