Abstract
We study two probabilistic models developed in order to predict the computational complexity of the branch and bound algorithm as well as its suitability for a parallelization based on the simultaneous exploration of all subproblems having a same common lower bound We show that both models, starting from different assumptions, yield asymptotically the same results but differ for small problems. Both models agree to predict a quick increase of the number of subproblems as a function of their lower bounds offering a convenient approach for parallelization of the branch and bound algorithm.
Work done as a Master's Thesis of ENS-Lyon, realized at EPFL.
Work supported by the SPP-IF program of the Swiss National Science Foundation.
Work realized during a longer visit at EPFL supported by the SPP-IF program.
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© 1994 Springer-Verlag Berlin Heidelberg
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Dion, M., Gengler, M., Ubéda, S. (1994). Comparing two probabilistic models of the computational complexity of the branch and bound algorithm. In: Buchberger, B., Volkert, J. (eds) Parallel Processing: CONPAR 94 — VAPP VI. VAPP CONPAR 1994 1994. Lecture Notes in Computer Science, vol 854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58430-7_32
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DOI: https://doi.org/10.1007/3-540-58430-7_32
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