Estimation of Number of Flight Using Particle Swarm Optimization and Artificial Neural Network

The number of flight (NF) is one of the key factors for the administration of the airport to evaluate the apron capacity and airline companies to fix the size of the flight. This paper aims to estimate the monthly NF by performing particle swarm optimization (PSO) and artificial neural network (ANN). Performed PSO-ANN algorithm aims to minimize the proposed evaluation criterion in the training stage. PSO-ANN based on the proposed evaluation criterion offers satisfying fitness values with respect to correlation coefficient and mean absolute percentage error in the training and testing stage

Time-Windowed Vehicle Routing Problem: Tabu Search Algorithm Approach

Vehicle routing problem (VRP); it is defined as the problem of planning the best distribution or collection routes of the vehicles assigned to serve the scattered centers from one or more warehouses in order to meet the demands of the customers. Vehicle routing problem has been a kind of problem in which various studies have been done in recent years. Many vehicle routing problems include scheduling visits to customers who are available during certain time windows. These problems are known as vehicle routing problems with time windows (VRPTWs). In this study, a tabu search optimization is proposed for the solution of time window vehicle routing problem (VRPTWs). The results were compared with the current situation and the results were interpreted