10:30 AM - 10:55 AM
A location problem for cash management centers
Banks manage cash logistics operations, such as satisfying cash needs of branches and ATMs or collecting extra cash and other valuables, through cash management centers (CMCs) located across the geography. In this talk, we present a mathematical program to optimally locate CMCs in a geographical market and discuss solution approaches.
10:55 AM - 11:20 AM
Branch-and-benders-cut algorithms for the single source capacitated facility location problem
We present two Benders decomposition schemes and a Benders-Branch-and-Cut based exact algorithm for the Single Source Capacitated Facility Location Problem (SSCFLP). In our implementation the Benders subproblems are formulated as set partitioning problems from which LP-based Benders cuts and canonical cuts are derived. Numerical results on benchmark instances demonstrate the effectiveness of the proposed algorithm in reasonable computation times.
11:20 AM - 11:45 AM
Formulations and approximation algorithms for multi-level facility location problems
We study multi-level uncapacitated p-location problems, a general class of facility location problems. We use a combinatorial representation of the general problem where the objective function satisfies the submodularity property, and we exploit this characterization to derive worst-case bounds for a greedy heuristic. We obtain sharper bounds when the setup cost for opening facilities is zero. Moreover, we introduce a mixed integer linear programming formulation for the problem based on the submodularity property. Some computational results are summarized in the presentation.
11:45 AM - 12:10 PM
Facility location under service level constraints for heterogeneous customers
We study the problem of locating service facilities to serve heterogeneous customers. Customers
requiring service are classified as either high priority or low priority, where high priority patients are always
served on a priority basis. The problem is to optimally locate service facilities and allocate their service
zones to satisfy the coverage and service level constraints defined based on waiting time distribution of each priority class. For this, we model the network of service facilities as spatially distributed priority queues, whose locations and user allocations need to be determined. The resulting integer programming problem is challenging to solve, especially in absence of any known analytical expression for the service level function of low priority customers. We develop a cutting plane based solution algorithm, exploiting the service level function of low priority customers to approximate
its non-linearity using tangent planes, determined numerically using matrix geometric method.