Traditionally, aircraft routing and crew pairing problems are solved sequentially with the aircraft routing problem solved first followed by the crew pairing problem. But in some cases, the results are suboptimal. In order to overcome this problem, both problems will be composed in one model. Although the integration model is challenging to solve but it is practically useful in airlines operations for getting the optimal solutions. In this study, we proposed the constructive heuristic method and the genetic algorithm (GA) in producing the feasible paths. After that, we will solve those two types of feasible paths in the integrated model by using three approaches which are the integer linear programming (ILP), Dantzig Wolfe decomposition method and Benders decomposition method. Computational results show that the obtained feasible path from the constructive heuristic method and solved by the Dantzig Wolfe decomposition method is more effective while the paths from the GA and solved by the Dantzig Wolfe decomposition method is good in finding the minimum computational time. From the results obtained, all the flight legs and crew pairing are used only once. There are four type of aircrafts are used in testing the performance of the approaches which based on local flights in Malaysia for seven days. The solutions of the feasible paths from GA is more advantageous in term of the computational times compare to the solutions by using the feasible paths from constructive heuristic method.

In airline operations planning, there are four problems which are schedule design, fleet assignment, aircraft routing and crew pairing problem. Those problems are sequentially and interdependent. Aircraft routing and crew pairing problem are hard to solve and normally crew pairing problem dependent to the aircraft routing problem which gives the suboptimal solutions. As minimizing the costs is important in the airline system, so in order to tackle suboptimal solutions, aircraft routing problem and crew pairing problem are being integrated in one model. For solving the integrated model, the feasible aircraft routes and crew pairs are required. Because of that, a method is being proposed in this work for generating the feasible aircraft routes and crew pairs which is the constructive heuristic method. By using the generic aircraft routes and crew pairs, the integrated model then being solve by two approaches. The first approach is the exact method called the integer linear programming (ILP) while the second approach is from the heuristic method called particle swarm optimization. Encouraging results are encountered by testing on four types of aircrafts for one week flight cycle from local flights in Malaysia.

Minimization of cost is very important in airline as great profit is an important objective for any airline system. One way to minimize the costs in airline is by developing an integrated planning process. Airline planning consists of many difficult operational decision problems including aircraft routing and crew pairing problems. These two sub-problems, though interrelated in practice, are usually solved sequentially leading to suboptimal solutions. We propose an integrated aircraft routing and crew pairing problem model, one approach to generate the feasible aircraft routes and crew pairs, followed by three approaches to solve the integrated model. The integrated aircraft routing and crew scheduling problem is to determine a minimum cost aircraft routes and crew schedules while each flight leg is covered by one aircraft and one crew. The first approach is an integer programming solution method, the second formulation is developed in a way to lend itself to be used efficiently by Dantzig Wolfe decomposition whereas the third one is formulated as a Benders decomposition method. Encouraging results are obtained when tested on four types of aircraft based on local flights in Malaysia for one week flight cycle.