Facility Location Problem In Network Optimization Process

The facility location problem is applyed widely in modern networkoptimization.correspondingly, many researches and literature has also described andmade summary about this, and had many important research results. This article willselect three typical site selection problems to dig in, and this article will also change theoptimistic objective or modify the algorithm, and analyse the results in detail.Topology design problem in early network building time, which alse called“equipment placed problem”, its math model “D/TNLLP1”, this article add switchcapacity constraint, edge capacity modulation constraint, and access connectionconstraint,multi-homing constraint, this article introduce two algorithm,simulatedannealing and simulated allocation, this article analysed the factors that affect results,this article compared the two algorithm.For the Hierarchical Traffic Grooming problem in WDM network problem, theoptimization goal is to minimize the number of carrying wavelengths required, to solvethe whole problem,we divide three steps,namely grouping network nodes; establish avirtual topology, route the virtual topology upon the physical layer, this article analysisand compare the results of several algorithms of classification,we also compare thestrengths and weaknesses of different algorithm and made great improvement to thealgorithm.In the last chapter, this article introduce the base station location problem, on meetwith the" least equipments cover model" and "maximum needs cover model", on "leastequipment cover model" situation, we use test points to simulate the wholecoverage-needed area. As the number of test points just began to increase, the needednumber of equipment gradually increased with it, but when the number increase more,the needed number of equipment tends to be stable.As is stated above, we mainly introduce the three scenes, they all perform goodlocation model to the facility location problem, moreover, their application situationsare very widely in network optimization.