I n this paper, we consider the multilevel capacitated minimum spanning tree (MLCMST) problem, a generalization of the well-known capacitated minimum spanning tree (CMST) problem, that allows for multiple facility types in the design of the network. We develop two flow-based mixed integer programming formulations that can be used to find tight lower bounds for MLCMST problems with up to 150 nodes. We also develop several heuristic procedures for the MLCMST problem. First, we present a savings-based heuristic. Next, we develop local search algorithms that use exponential size, node-based, cyclic and path exchange neighborhoods. Finally, we develop a hybrid genetic algorithm for the MLCMST. Extensive computational results on a large set of test problems indicate that the genetic algorithm is robust and, among the heuristics, generates the best solutions. They are typically 6.09% from the lower bound and 0.25% from the optimal solution value.

In this article, we consider the notion of "reload costs" in network design. Reload costs occur naturally in many different settings including telecommunication networks using diverse technologies. However, reload costs have not been studied extensively in the literature. Given that reload costs occur naturally in many settings, we are motivated by the desire to develop "good" models for network design problems involving reload costs. In this article, and as a first step in this direction, we propose and discuss the reload cost spanning tree problem (RCSTP). We show that the RCSTP is NP-complete. We discuss several ways of modeling network design problems with reload costs. These involve models that expand the original graph significantly-to a directed line graph and a colored graph-to model reload costs. We show that the different modeling approaches lead to models with the same linear programming bound. We then discuss several variations of reload cost spanning tree and network design problems, and discuss both their complexity and models for these variations. To assess the effectiveness of the proposed models to solve RCSTP instances, we present results taken from instances with up to 50 nodes, 300 edges, and nine technologies for several variations of the problem.

No abstract

Capacitated network design is a crucial problem to telecommunications network planners. In this paper we consider the Multi-Level Capacitated Minimum Spanning Tree Problem (MLCMST), a generalization of the well-known Capacitated Minimum Spanning Tree Problem. We present a genetic algorithm, based on the notion of grouping, that is quite effective in solving large-scale problems to within 10% of optimality.

Catholic Relief Services, a not-for-profit agency that funds development programs and humanitarian relief efforts throughout the world, faces a challenging budget-allocation problem annually. We developed a mathematical model and a spreadsheet tool that allocates available funds based on the impact these investments will have in different countries. The model ensures a fair allocation to countries in need that is consistent with the agency's priorities and is simple enough for managers to understand. The agency is using the tool to plan its spending and considers it a success that has greatly improved the planning process.