Study of fleet assignment problem using a hybrid technique based on Monte Carlo simulation and genetic algorithm

Fleet assignment problem (FAP) is the assignment of an aircraft model to each scheduled flight based on key operational variables such as cost, revenue, passenger travel demand and aircraft specifications. FAP is an important aspect of aircraft planning within an airline. While many developed economy have automated this planning task, developing economy such as Nigeria mainly depend on manpower to carry out this task. The aim of this paper is to solve a FAP using a hybrid technique based on the combination of Monte-Carlo (MC) simulation and Genetic Algorithm (GA). The objective function is total cost and variation in aircraft models and passenger traffic associated with different scheduled flight were considered. MC simulation which was carried out based on the numerical approximation of normal distribution cumulative distribution function (cdf) was used to estimate the expected passenger spill rate, while genetic algorithm was used for the optimization. The result was found to be satisfactory, as optimal fleet plan was achieved in approximately fifteen seconds of program run time, as against not less than an hour usually spend using human effort to solve FAP. Also the optimized plan resulted to a thirty percent saving in comparison to the actual plan implemented by the airline. It is therefore recommended that MC-GA optimization technique should be considered as an alternative technique applicable for FAP optimization.Keywords: Fleet assignment, genetic algorithm Monte-Carlo simulation, optimizatio

Propensity to fly in Nigeria: a forecast of domestic air passenger traffic flow in some Nigeria airports

This study carried out an assessment of the air passenger traffic flow in some airports in the six geopolitical zones of Nigeria. Secondary data used in the study was collected from Federal Airport Authority of Nigeria (FAAN) database. Time series features were studied using time series plot and autocorrelation plot against time lag. The forecasting capability of multiplication and additive decomposition models were compared to those of additive and multiplication Holt’s Winter methods and the prediction of passenger volume was based on the model with the lowest Mean Square Deviation (MSD) value. The result revealed that Abuja, Kano, Owerri and Yola airports showed upward trend, while Lagos and Port-Harcourt airports showed downward trend. The entire airports with the exception of Yola airport were found to be stationary. The 2017 and 2018 forecast on passenger traffic shows a consistence increase in the total passenger volume for Owerri, Kano and Abuja airports, while Lagos, Yola and Port-Harcourt airports shows slight decrease in the total passenger volume. Based on the results, airport investors should consider investment in Owerri, Kano and Abuja airports, as these airports shows a promising increase in passenger traffic.Keywords: Airport, Decomposition method, Forecast, Holt’s winter method, Passenger travel demand, Time series analysi