Review on meta-heuristics approaches for airside operation research

Abstract

The number of publications related to airside operations research is increasing and gaining in popularity. This paper aims to provide researchers with a comprehensive and extensive overview of meta-heuristics application for aviation research, with a particular focus on the airside operations. The scope of airside operations research covers airspace and air traffic flow management, aircraft operation in the terminal manoeuvring area and surface traffic operation. Based on the recent publications related to airside operations, the meta-heuristics approach is a promising approach to enhance the computational efficiency and achieve higher applicable in various decisions in airside operations. However, the literature on airside operations research is quite disjointed and disparate. Therefore, a general taxonomy framework for the airside information system is proposed in order to classify the research systematically and expedites related research and development of engineering applications in the aviation industry. To the best of our knowledge, this is the first review of the field using the meta-heuristics approach. The prominent findings of recent publication and the directions of future research are addressed throughout the review and analysis of the relevant studies.

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

“…In order to reduce fuel consumption and exhaust emissions during taxiing on the airport surface, push-back control strategy [11,12], taxiing trajectory and speed profile optimizations [13,14], and improvement of taxiing mode (e.g., single-engine taxiing, operational tow-outs, and electric taxiing) [15,16] have been comprehensively investigated. During climb and descent, especially in high-density terminal airspace, prior research has focused more on how to make full use of runway capacity, while minimizing noise, total fuel consumption, emissions, and delays [17][18][19], and put forward operating concepts and operating procedures such as Continuous Climbing Operation (CCO) [20], Continuous Descending Operation (CDO) [21], Point Merge (PM) [22], etc.…”

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

“…Airside operation research covers different fields in air transport management, including airspace and air traffic flow management, aircraft operation in the terminal maneuvering area, and surface traffic operation [25] . Högdahl et al [26] developed a simulation-optimization approach to minimize travel time and delays in railway timetables.…”

Rule Induction with Iterated Local Search

“…Different methods have been considered in the literature when designing a metaheuristic algorithm [10]. Those methods include forbidden areas in the feasible search region (e.g., tabu search), involving the acceptance of worsen solution during the search operations (e.g., simulated annealing), the active principle of populations-based solutions (i.e., evolutionary algorithms), the application of penalties in the search operations as used in the dynamic local search methods, or the concept of swarm intelligent such as used in particle swarm optimization, and ant colony optimization approaches [11].…”