Equitable Conflict-Free Slot Allocation Based on Constraint Programming and Multicriteria Optimization

The increasing complexity of air traffic management presents critical challenges in balancing operational efficiency and equitable resource allocation. As global air traffic continues to grow, traditional conflict resolution methods struggle to effectively manage trajectory conflicts and minimize delays across multiple operators. This paper introduces an innovative constraint programming (CP) approach that leverages ordered weighted averaging, minimum deviation, and augmented minimum deviation multicriteria aggregation operators to optimize takeoff slot allocation while ensuring fairness. The proposed methodology addresses key challenges through i) an advanced CP optimization model minimizing delays while ensuring equitable distribution; ii) a novel large neighborhood search (LNS) strategy for efficient solution space exploration; and iii) a symmetry-breaking mechanism to reduce computational complexity. Experimental validation using simulated flight data demonstrates the approach’s superior performance. The results show significant improvements in delay distribution and operational efficiency (minimizing total delays) compared to traditional optimization methods. By providing a robust framework for multicriteria optimization in air traffic management, this research offers a practical solution to the increasing challenges of modern aviation, ultimately contributing to more efficient and equitable air transportation systems.