A review of dynamic vehicle routing problems by Victor Pillac, Michel Gendreau, Christelle Guéret, and Andrés Medaglia discusses the evolution and quality of information in dynamic routing problems. The paper classifies routing problems based on these dimensions and presents a comprehensive review of applications and solution methods for dynamic vehicle routing problems. It introduces the concept of degree of dynamism, which measures the proportion of dynamic requests relative to total requests. The paper also explores different types of dynamic routing problems, including those with stochastic demands, time windows, and varying vehicle availability. It reviews various applications such as emergency services, city logistics, and transport of goods and persons. The paper also discusses solution methods for dynamic routing problems, including periodic and continuous reoptimization approaches, as well as stochastic modeling and sampling techniques. The paper concludes that dynamic routing problems require real-time decision-making and specialized solution methods to handle the complexity introduced by dynamic information. The authors emphasize the importance of developing efficient algorithms and decision support systems for dynamic routing problems.A review of dynamic vehicle routing problems by Victor Pillac, Michel Gendreau, Christelle Guéret, and Andrés Medaglia discusses the evolution and quality of information in dynamic routing problems. The paper classifies routing problems based on these dimensions and presents a comprehensive review of applications and solution methods for dynamic vehicle routing problems. It introduces the concept of degree of dynamism, which measures the proportion of dynamic requests relative to total requests. The paper also explores different types of dynamic routing problems, including those with stochastic demands, time windows, and varying vehicle availability. It reviews various applications such as emergency services, city logistics, and transport of goods and persons. The paper also discusses solution methods for dynamic routing problems, including periodic and continuous reoptimization approaches, as well as stochastic modeling and sampling techniques. The paper concludes that dynamic routing problems require real-time decision-making and specialized solution methods to handle the complexity introduced by dynamic information. The authors emphasize the importance of developing efficient algorithms and decision support systems for dynamic routing problems.