By Sbihi A.
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Extra info for A best first search exact algorithm for the Multiple-choice Multidimensional Knapsack Problem
Deterministic) length chromosomes. The chromosomes in the algorithm are sequences of integers and each gene represents a node ID, that is selected randomly from the set of nodes connected with the node corresponding to its locus number. All the chromosomes have the same (ﬁxed) length. In the crossover phase, one of the genes from two parent chromosomes is selected at the locus of the starting node ID and put in the same locus of an oﬀspring. One of the genes is then selected randomly at the locus of the previously chosen gene’s number.
GA hardware, on the other hand, scales well to networks that may not even ﬁt within the memory. It is realized by employing parallel GA over several nodes. Therefore, GAs (especially hardware implementations) are clearly quite promising in this regard. 2 Existing GA-Based Approaches Investigators have applied GAs to unicasting SP routing problem [57, 67, 79], multicasting routing problem [118, 120], ATM bandwidth allocation problem , capacity and ﬂow assignment problem , and the dynamic routing problem .
Here, A and B are domain-dependent constants. 0. 8) Therefore, the average order may be calculated as follows: k = 1 · c1 + 2 · c2 = 1 + c2 = 1 + 10−2 · (1 − α)2 · |V|. 9) From Eq. 9), we can see that the average order k is around 1 if the network does not have a large number of nodes. In that case, the probability of disruption of the BBs by crossover is very small. It is noted that if the average order k becomes large, the probability becomes large too and the population size might be aﬀected.
A best first search exact algorithm for the Multiple-choice Multidimensional Knapsack Problem by Sbihi A.