An Efficient Algorithm for Solving the Applied Problem Scheduling Optimization of a Parallel-Sequential System

The problem of optimal regulation of airline fleet schedules by reassigning aircraft to flights is considered. The optimal regulation of schedules is to create or change them in such a way that minimizes system losses due to current violations. As an estimate of losses, the total deviation of the adjusted schedule from the spetified departure schedules of aircraft is used. It is shown that the described technological system belongs to the category of parallel-sequential systems. Accordingly, the considered system control problem is NP-hard and does not have effective algorithms for exact solution. A brief overview of approaches to solving its modifications and related fleet management tasks is given. The original formal formulation is given, the decomposition of the problem is justified, and an algorithm for its approximate solution is presented. An illustrative example is given and comparative statistics of testing software implementations of the decomposition algorithm of the schedule control problem on real data are reflected, proving the actual effectiveness of the developed tools.

Two-Phase Heuristic Algorithm for Integrated Airline Fleet Assignment and Routing Problem

High profitability and high costs have stiffened competition in the airline industry. The main purpose of the study is to propose a computationally efficient algorithm for integrated fleet assignments and aircraft routing problems for a real-case hub and spoke airline planning problem. The economic concerns of airline operations have led to the need for minimising costs and increasing the ability to meet rising demands. Since fleets are the most limited and valuable assets of airline carriers, the allocation of aircraft to scheduled flights directly affects profitability/market share. The airline fleet assignment problem (AFAP) addresses the assignment of aircraft, each with a different capacity, capability, availability, and requirement, to a given flight schedule. This study proposes a mathematical model and heuristic method for solving a real-life airline fleet assignment and aircraft routing problem. We generate a set of problem instances based on real data and conduct a computational experiment to assess the performance of the proposed algorithm. The numerical study and experimental results indicate that the heuristic algorithm provides optimal solutions for the integrated fleet assignment and aircraft routing problem. Furthermore, a computational study reveals that compared with the heuristic method, solving the mathematical model takes significantly longer to execute.

Particle swarm optimization for airlines fleet assignment

Airline fleet assignment is the process of assigning aircraft types to scheduled flight legs in order to minimize operating cost and achieve maximize revenue, while satisfying a set of constraints. This paper formulate the fleet assignment problem for airlines that optimization goal is to minimize the total assignment cost. Particle swarm optimization proposed to solve this model. The model successfully applied to Egyptair airline dataset using the particle swarm optimization and mixed integer programming. The proposed method compared with mixed integer programming and current Egyptair assignment methodology. The results showed that the particle swarm optimization is the best method for the Egyptair fleet assignment process. The solution quality is better than mixed integer programming and Egyptair assignment methodology where we saw a daily cost reduction with a percentage of 14.6% and 19.3% respectively.