10h30 - 10h55
Lagrangean Relaxation for p-Hub Arc Location Problems with Isolated Hubs
In this talk we present p-Hub Arc Location Problems with Isolated Hub nodes. We develop a Lagrangean relaxation algorithm that exploits the structure of a path-based formulation to efficiently obtain lower and upper bounds on the optimal solution value. Computational results on instances with up to 100 nodes are reported.
10h55 - 11h20
Exact and Heuristic Algorithms for the Multiple Hub Line Location Problem
We present solution algorithms for a hub location problem in which one must locate hub nodes and arcs so that the resulting network forms a set of lines. The problem arises, e.g., in the design of rapid transit systems comprising several intersecting lines. We introduce a Benders decomposition to compute lower bounds on the optimal solution value as well as meta-heuristics to obtain good feasible solutions. Computational results are reported on instances with up to 70 nodes and three lines.
11h20 - 11h45
Hub Network Design Problems with Profits
In this talk we present Hub location Problems with Profits, where it is not necessary to provide service to all demand nodes. A profit is associated with each flow between pair of nodes. The goal is the simultaneous optimization of the collected profit, the set-up cost of the hub network and the routing cost for routing the flow. Potential applications appear in the design of airline and ground transportation networks. Mathematical models and a unifying Lagrangean relaxation approach are presented to solve this class of problems. Numerical results on a set of benchmark instances are reported.
11h45 - 12h10
Robust Uncapacitated Hub Location
In this talk we present robust uncapacitated hub location problems in which uncertainty is associated with demands and transportation costs and modeled with a budget of uncertainty set. We study three robust counterparts of the well-known uncapacitated hub location problem with multiple assignments. The first focuses on demand uncertainty, the second one deals with transportation cost uncertainty and the third one considers both demand and transportation cost uncertainty. Computational experiments are reported.