Q3. (10 points) Consider the problem of a constrained MST Given a weighted, undi
ID: 3740142 • Letter: Q
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Q3. (10 points) Consider the problem of a constrained MST Given a weighted, undirected graph G=(VE), and given a subset of vertices C C V, describe a method to find a constrained MST such that vertices in C only appear as leaves in the constrained MST What is the running time of your algorithm? Note that for some choice of C, it may be the case that the constraint cannot be satisfied, i.e., it may be the case that there is at least one vertex in C that cannot be made a leaf node. In these cases, you can output that the constraint cannot be satisfiedExplanation / Answer
Given an undirected, associated, weighted chart, the leaf-obliged least traversing tree (LCMST) issue looks for a crossing tree of least weight among all the spreading over trees of the diagram with at any rate l takes off. In this paper, we have proposed an approach in light of Quantum-Behaved Particle Swarm Optimization (QPSO) for the LCMST issue. Molecule swarm advancement (PSO) is a notable populace based swarm insight calculation. Quantum-carried on molecule swarm streamlining (QPSO) is likewise proposed by joining the established PSO rationality and quantum mechanics to enhance execution of PSO. In this paper QPSO has been changed by including a jumping conduct. At the point when the changed QPSO (MQPSO), falls in to the nearby ideal, MPSO runs a jumping conduct to jump out the neighborhood ideal. We have looked at the execution of the proposed strategy with ML, SCGA, ACO-LCMST, TS-LCMST and ABC-LCMST, which are accounted for in the writing. Computational outcomes exhibit the predominance of the MQPSO approach over the various methodologies. The MQPSO approach acquired better quality arrangements in shorter time.
Given an undirected, associated, weighted diagram, the leaf-compelled least traversing tree (LCMST) issue looks for on this chart a spreading over tree of least weight among all the crossing trees of the diagram that have in any event takes off. In this paper, we have proposed a fake honey bee province (ABC) calculation for the LCMST issue. The ABC calculation is another metaheuristic approach enlivened by insightful scavenging conduct of bumble bee swarm. We have thought about the execution of our ABC approach against the best methodologies detailed in the writing. Computational outcomes show the prevalence of the new ABC approach over the various methodologies. The new approach got better quality arrangements in shorter time.
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