Multiple Objective Optimization of Highway Alignments Incorporating Preference Information

Decision making with regard to highway alignment design should consider trade-offs among diverse objectives, such as between environmental impacts and alignment cost. This paper presents a multiple objective optimization model for assisting highway designers in preparing alignment alternatives attractive to decision makers. A Hybrid Multi-Objective Genetic Algorithm (HMOGA) which utilizes designers' knowledge about the preferences of decision makers is developed to search for a set of desirable Pareto-optimal solutions with an acceptable level of diversity. A case study confirms the capability of the proposed methodology in providing multiple high-quality trade-off solutions. The results clearly indicate that the incorporation of preference information, even if preliminary in nature, can significantly improve the quality of obtained Pareto-optimal set.