Abstract
The Genetic Algorithm (GA) is a powerful technique that has been applied with fair success to various optimization problems. In this chapter, we discuss two ways of significantly improving the power of the GA: choosing a representation of solutions that reflects the structure of the problem being optimized, and using a powerful local optimization. The impact of these improvements is illustrated on a combinatorial problem of considerable industrial importance, the Bin Packing Problem (BPP).
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Falkenauer, E. (1995). Tapping the Full Power of Genetic Algorithm through Suitable Representation and Local Optimization: Application to Bin Packing. In: Biethahn, J., Nissen, V. (eds) Evolutionary Algorithms in Management Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-61217-6_8
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DOI: https://doi.org/10.1007/978-3-642-61217-6_8
Publisher Name: Springer, Berlin, Heidelberg
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