Abstract. We consider two-dimensional cutting stock problems where single rectangular stocks have to be cut into some smaller rectangular so that the number of stocks needed to satisfy the demands is minimum. In this paper we focus our study to the problem where the stocks have to be cut with guillotine cutting type and fixed orientation of finals. We formulate the problem as an integer programming, where the relaxation problem is solved by column generation technique. New pattern generation is formulated based on method of stripe. In obtaining the integer solution, we round down the optimal solution of the relaxation problem and then we derive an extra mix integer programming for satisfying the unmet demands. The optimal solution of the original problem is the combination of the round-down solution and the optimal solution of the extra mix integer programming.A numerical example of the problem is given in the end of this paper.
Abstract. This paper discusses Indonesia, taking into account regulations. These internal labor regulations are in general more restrictive at Garuda Indonesia than at other airlines, so that modeling the cockpit crew rostering problem for Garuda Indonesia is challenging. We ha mathematical expressions for the cockpit crew labor regulations and some technical matters. We model problem, using the average relative deviation of total flight time to the ideal flight time as the objective function. for all classes of cockpit crews of Garuda Indonesia, using a simulated annealing method for solving the problem. We obtained satisfactory ro members in a short amount of computing time. This shows that the optimization problem is well-defined.
The airline crew pairing problem is one of the optimization problems which classified as a NP-hard problem. Since the number of feasible pairings in flight schedules can be numerous, the exact methods will not efficient to solve the problem. We propose a heuristic method for solving crew pairing problems. Initially, we generate a feasible solution by maximizing the covered flights. Then, we improve the solution by constructing a procedure to avoid the local optimal solution. We test our method to an airline schedules. The computational results show that our method can give the optimal solution in short period of time.
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