Whale Optimization Algorithm for Airport Gate Assignment Problem

Abstract

AbstractIn view of the rapid increase in the volume of air traffic, optimization of airport management has recently gained a great deal of attention to be able to increase the airport capacity and efficiently use scarce resources, namely gates. Improper assignment of gates causes flight delays, inefficient usage of scarce resources, customers’ dissatisfaction and other domino effects. Generally, a typical hub-and-spoke handles hundreds of flights every day. Considering this, the gate assignment problem (GAP) addresses the issue of maximizing the usage of gates equipped with aerobridges, namely bridge-equipped gates. Due to the numerous flights and gates involved in the problem, it is often impractical to solve GAP with optimality in a reasonable amount of computational time. Consequently, novel nature-inspired heuristics have been proposed to generate good solutions to AGAP. In this study, we employ Whale Optimization Algorithm (WOA) which is one of the recently developed swarm-based metaheuristics to find good solutions to complex GAP. The proposed method assigns scheduled flights to bridge-equipped gates based on both total flight-to-gate assignment utility and use of apron gates. In order to demonstrate the efficiency of the algorithm, some instances with different sizes are generated and the results obtained by using CPLEX Studio IDE optimizer and WOA are compared with respect to solution quality and computational time. To ameliorate the solution quality, we proposed two local search procedures embedded in WOA. To the best of our knowledge, WOA has never been applied to GAP so far. Thus, the chief contribution of this study is to apply such novel swarm-based metaheuristic, namely WOA to GAP. Comparison of the results with the optimal schedules has allowed us to demonstrate the power of the proposed algorithm.KeywordsWhale optimization algorithmAirport gate assignment problemMeta-heuristicsLocal search