A technique for efficient multimodal transport planning with conflicting objectives under uncertainty

Multimodal freight transport is growing as a means to reduce environmental impact and road congestion, and to increase road safety. The proper planning and management of multimodal transport is a key issue to ensure the competitiveness of companies. In this paper we present a fuzzy cross-efficiency Data Envelopment Analysis (DEA) technique for efficient multimodal transport planning in a multi-objective perspective, under uncertainty, and with a high discriminative power. The approach is tested on a real case study, showing its effectiveness in determining the most efficient transport planning and in identifying the distance from which multimodality is more efficient than all-road transport.