mcMST (version 1.0.1)

genRandomMCGP: Generate a bi-criteria graph with uniformly randomly distribted edge weights.

Description

No topology is defined. The instance is composed of two symmetric weight matrices. The first weight is drawn independently at random from a \(\mathcal{R}[10, 100]\) distribution, the second one from a \(\mathcal{R}[10, 50]\) distribution (see references).

Usage

genRandomMCGP(n)

Value

[mcGP]

Arguments

n

[integer(1)]
Instance size, i.e., number of nodes.

References

Zhou, G. and Gen, M. Genetic Algorithm Approach on Multi-Criteria Minimum Spanning Tree Problem. In: European Journal of Operational Research (1999).

Knowles, JD & Corne, DW 2001, A comparison of encodings and algorithms for multiobjective minimum spanning tree problems. in Proceedings of the IEEE Conference on Evolutionary Computation, ICEC|Proc IEEE Conf Evol Comput Proc ICEC. vol. 1, Institute of Electrical and Electronics Engineers , pp. 544-551, Congress on Evolutionary Computation 2001, Soul, 1 July.

Examples

g = genRandomMCGP(10L)
if (FALSE) {
pl = plot(g)
}