An investigation of a tabu assisted hyper-heuristic genetic algorithm

This paper investigates a tabu assisted genetic algorithm based hyperheuristic (hyperTGA) for personnel scheduling problems. We recently introduced a hyperheuristic genetic algorithm (hyperGA) with an adaptive length chromosome which aims to evolve an ordering of low-level heuristics in order to find good quality solutions to given problems. The addition of a tabu method, the focus of this paper, extends that work. The aim of adding a tabu list to the hyperGA is to indicate the efficiency of each gene within the chromosome. We apply the algorithm to a geographically distributed training staff and course scheduling problem and compare the computational results with our previous hyperGA.

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