A Genetic Algorithm for the Set Partitioning Problem

In this paper we present a genetic algorithm-based heuristic for solving the set partitioning problem. The set partitioning problem is an important combinatorial optimisation problem used by many airlines as a mathematical model for ight crew scheduling. We develop a steady-state genetic algorithm in conjunction with a specialised heuristic feasibility operator for solving the set partitioning problem. Some basic genetic algorithm components, such as tness deenition, parent selection and population replacement are modiied. The performance of our algorithm is evaluated on a large set of real-world set partitioning problems provided by the airline industry. Computational results show that the genetic algorithm-based heuristic is capable of producing high-quality solutions. In addition a number of the ideas presented (separate tness, unntness scores and subgroup population replacement) are applicable to any genetic algorithm for constrained problems.

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