A Multi Model Algorithm for the Cost Oriented Design of the Information Technology Infastructure

Multiple combinations of hardware and network components can be selected to design an information technology (IT) infrastructure that satisfies performance requirements. The professional criterion to deal with these degrees of freedom is cost minimization. However, a scientific approach has been rarely applied to cost minimization and a rigorous methodological support to cost issues of infrastructural design is still lacking. The methodological contribution of this paper is the representation of complex infrastructural design issues as a set of four intertwined cost-minimization sub-problems: two set-coverings, a set-packing and a min k-cut with a non linear objective function. Optimization is accomplished by sequentially solving all sub-problems with a heuristic approach and finally tuning the solution with a local-search approach. The methodology is empirically verified with a software tool including a database of costs that has also been built as part of this research. The work shows how an overall costminimization approach can provide significant savings and indicates how corresponding infrastructural design rules can substantially differ from the local optima previously identified by the professional literature

A local search based heuristic for the demand constrained

We consider an extension of the 0-1 multidimensional knapsack problem in which there are greater-than-equal inequalities, called demand constraints, besides the standard less-than-equal constraints. Moreover the objective function coefficients are not constrained in sign. This problem is worth considering because it is embedded in the models of practical applications, because it has an intriguing combinatorial structure and because it appears to be a challenging problem for commercial ILP solvers. Our approach is based on a nested tabu search algorithm in which neighbourhoods of different structure are exploited. A first higher level tabu search is carried on in which both feasible and unfeasible regions are explored. In this diversification phase an oscillation method proceeds alternating between constructive and destructive steps. Occasionally, a lower level tabu search which implements an intensification strategy is applied. In this second phase only feasible solutions are analysed. The algorithm has been tested on a wide set of instances. Computational results are discussed

Channel Assignment Problem in Cellular Systems: A New Model and a Tabu Search Algorithm

The channel assignment in cellular systems has the task of planning the reuse of available frequencies in a spectrum efficient way. A classical approach to frequency assignment problems, when applied to the frequency planning of cellular networks, does not enable this task to be performed in an efficient way, since it does not consider the cumulative effect of interferers. In the paper, we propose a new model for the channel assignment problem in narrow-band cellular networks, which accounts for the cumulative effect of interferers. In this model, the service area is partitioned into regions and the propagation characteristics are assigned by means of the levels received in each region by the considered base stations (BS's). The objective is to maximize the sum of traffic loads offered by regions in which the ratio between the received power and the sum of powers received from interfering transmissions is above a threshold value. In the paper, we also present an algorithm, based on tabu search (TS) techniques, to solve this problem. This algorithm has been tested on some instances obtained by using a simple radio channel model and on a real world instance

A Cost-oriented Approach for Infrastructural Design

The selection of a cost-minimizing combination of hardware and network components that satisfy organizational requirements is a complex design problem with multiple degrees of freedom. Decisions must be made on how to distribute the overall computing load onto multiple computers, where to locate computers and how to take advantage of legacy components. The corresponding optimization problem not only embeds the structure of NP-hard problems, but also represents a challenge with a well-structured heuristic approach. A scientific approach has been rarely applied to cost minimization and a rigorous methodological support to cost issues of infrastructural design is still lacking. The methodological contribution of this paper is the representation of complex infrastructural design issues as a single cost-minimization problem. The problem is decomposed in four interwined cost-minimization sub-prolems; optimization is accomplished by sequentially solving these sub-problems with a heuristic approach and tuning their solution with a final tabusearch step. Results indicate that decomposition significantly reduces optimization time and solutions are also closer to the global optimum if results are compared to those identified without prior decomposition. Cost reductions are also significant when practicioners' solutions, obtained by applying simplified design rules from the professional literature, are considered