Pareto Evolutionary Optimization of Joint Network Design and Pricing Strategies Related to Emissions in Urban Networks

In the current social, physical, economical and environmental circumstances of scarcity, the design and management of vital lifelines like transportation systems, especially within the metropolitan context, are subject to the implementation of multiple objectives in a unified framework. Thus, one of the most important issues is the identification of optimal trade-offs among crucial objectives both from the designer's as well as from the users' perspective. In the current study a comprehensive framework for estimating optimal interrelations and dilemmas among emissions-related carbon footprint and other (social- and economic-related) features of urban road networks design and operation are presented and analyzed, based on techniques of multi-objective and hierarchical mathematical programming with equilibrium constraints, solved by suitable hybridization of evolutionary algorithms. The results of the proposed optimization methodological approach provide the Pareto Frontier of solutions, which corresponds to optimal trade-offs amongst multiple objectives. The computational experience from the application of the proposed methodological approach on a part of a realistic urban network is presented, providing evidence on the applicability as well as on the computational burden of such transportation design paradigms, but most importantly, on the dilemmas emerging in sustainable design and planning of transportation systems.