Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Uniform crossover in genetic algorithms
Proceedings of the third international conference on Genetic algorithms
A genetic algorithm for the generalised assignment problem
Computers and Operations Research
A Comparison of Parallel and Sequential Niching Methods
Proceedings of the 6th International Conference on Genetic Algorithms
Fitness sharing and niching methods revisited
IEEE Transactions on Evolutionary Computation
Comparative analysis of the sailor assignment problem
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
A multiobjective evolutionary algorithm for the task based sailor assignment problem
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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This paper examines a real-world application of genetic algorithms -- solving the United States Navy's Sailor Assignment Problem (SAP). The SAP is a complex assignment problem in which each of n sailors must be assigned one job drawn from a set of m jobs. The goal is to find a set of these assignments such that the overall desirability of the match is maximized while the cost of the match is minimized. We compare genetic algorithms to an existing algorithm, the Gale-Shapley algorithm, for generating these assignments and present empirical results showing that the GA is able to produce good solutions with significant savings in cost. Finally, we examine the possibility of using the GA to generate multiple different solutions for presentation to a human decision maker called a detailer, and we show that the GA can be used to provide a sample of good solutions.