Crew scheduling problem is one of the hardest and most comprehensive problems encountered in airline planning. In crew scheduling problem, it is aimed to find the minimum costly set of pairings in that each flight leg...
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Crew scheduling problem is one of the hardest and most comprehensive problems encountered in airline planning. In crew scheduling problem, it is aimed to find the minimum costly set of pairings in that each flight leg is covered at least by one crew pairing. In this study, a columngeneration approach that is commonly used in crew scheduling literature in which variables are dynamically generated, is used to solve the problem. The master problem is formulated as a set covering problem while the subproblem is formulated as a shortest path problem. Initial pairings which are sufficient to obtain a feasible solution, are produced using a linear programming model. The master problem, sub-problem and the model used to generate initial pairings are encoded by GAMS optimization program in an integrated manner and this integrated model is solved iteratively. The algorithm is applied to a private airline company's crew scheduling problem using real data and optimal crew schedules are obtained.
A heuristic combining the columngeneration technique and a genetic algorithm is proposed for solving the problem of preemptive scheduling in a two-stage flowshop with parallel unrelated machines and renewable resourc...
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ISBN:
(纸本)9728865597
A heuristic combining the columngeneration technique and a genetic algorithm is proposed for solving the problem of preemptive scheduling in a two-stage flowshop with parallel unrelated machines and renewable resources at the first stage and a single machine at the second stage. The objective is to minimize the makespan. The lower bound on the optimal makespan is derived to be used in the performance analysis of the heuristic. The performance of the heuristic is analyzed by a computational experiment. The results show that the heuristic is able to find near-optimal solutions in reasonable computation time.
This paper considers the problem of the scheduling of preemptive jobs on unrelated parallel machines, which differs from those discussed in the literature in that it includes changeovers of machines as well as tempora...
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This paper considers the problem of the scheduling of preemptive jobs on unrelated parallel machines, which differs from those discussed in the literature in that it includes changeovers of machines as well as temporary constraints of resources. This problem is complicated to such an extent that even its mathematical formulation seems impossible. Its solution calls therefore for the introduction of some heuristics. The paper presents a two-stage heuristic integrating the columngeneration technique with a genetic algorithm for the purpose of minimizing the makespan and the total cost of changeovers. The quality of this heuristic is evaluated by comparing the solutions to a lower bound on the objective function optimal value. An integer-linear programming procedure determining the lower bound is proposed. Extensive experimental study shows that the two-stage heuristic presented is effective for medium-size problems with strong temporary resource constraints in the case of the total cast of changeovers being not in excess of 10% of the makespan cost. (C) 1999 Elsevier Science Ltd. All rights reserved.
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