Scheduling aircraft landing is a complex task encountered by most of the control towers. In this paper, we study the aircraft landing problem (ALP) in the multiple runway case. We present in the first part, a mathematical formulation of the problem with a linear and nonlinear objective function. In the second part, we consider the static case of the problem where all data are known in advance and we present a new heuristic for scheduling aircraft landing on a single runway, this heuristic is incorporated into an ant colony algorithm to solve the multiple runway case.
The Vehicle Routing Problem (VRP) is an important problem occurring in many logistics systems.The obj ective of VRP is to serve a set of customers at minimum cost, such that every node is visited by exactly one vehicle only once. In this paper, we consider the Dynamic Vehicle Routing Problem (DVRP) which new customer demands are received along the day. Hence, they must be serviced at their locations by a set of vehicles in real time minimizing the total travel distance. The main goal of this research is to find a solution of DVRP using genetic algorithm. However we used some heuristics in addition during generation of the initial population and crossover for tuning the system to obtain better result. The computational experiments were applied to 22 benchmarks instances with up to 385 customers and the effectiveness of the proposed approach is validated by comparing the computational results with those previously presented in the literature.
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