Optimizing Aircraft Fleet Assignment in Airline Route Networks Using a GA-Based Allocation with Greedy Chain Assignment under Operational Constraints

Abstract

The fleet assignment problem remains a critical challenge in airline operations, where heterogeneous aircraft must be allocated to scheduled flights in a manner that minimizes total costs while satisfying operational constraints. This paper formulates the problem as a cost minimization model that incorporates both operating expenses and passenger spill costs under constraints of fleet size, airport balance, and time-space network feasibility. Due to the combinatorial nature of the problem, traditional method often faced with poor scalability when increase problem size. To address this, we propose a Genetic Algorithm (GA)-based approach enhanced with a greedy chain assignment and repa ir mechanism to efficiently enforce airport balance and availability constraints. Numerical evaluations are conducted on small-scale and large-scale test cases under multiple cost-per-available-seat-mile (CASM) scenarios. The numerical evaluation highlights the effectiveness and adaptability of the proposed GA-based framework in solving fleet assignment problems