This study develops a framework for a multimodal transportation system comprising two different modes of transportation—airways and roadways within a multi-echelon supply chain network in B2C e-commerce platforms. In this study, an optimization model based on mixed-integer quadratic programming was formulated, the objective of which is to minimize the overall transportation cost for B2C e-commerce supply chain networks. The metaheuristic technique incorporating two varied approaches—exact optimization and a genetic algorithm—was employed to provide the solution for this proposed optimization model of multimodal transportation system. This metaheuristic technique-based optimization model was tested on simulated datasets created to develop and analyze different case scenarios for the stated multimodal transportation problem. The comparative analysis of these two solution approaches is provided from the perspective of experimental performance as well as theoretical consideration. The findings of study can be applied to multi-echelon multimodal transportation networks in real practices targeting overall cost reduction and profit maximization of the logistic services for B2C e-commerce platforms.