03:30 PM - 03:55 PM
An exact method for hub network design problems with profits
In this talk we present Hub Network Design Problems with profits where it is not necessary to provide service to all demand nodes. We propose a branch-and-bound algorithm that uses a Lagrangian relaxation to obtain lower and upper bounds at the nodes of the tree. Numerical results on a set of benchmark instances are reported.
03:55 PM - 04:20 PM
Slope scaling for multilayer network design problem
In multilayer network design multiple parallel layers of networks have to be considered simultaneously. A network has to be designed in each layer to transfer the commodities. To open a link in a particular layer, a chain of supporting links (path) in another layer has to be opened or designed. This integration of multiple layers can yield an optimized multilayer network that cannot be obtained by solving individual network design problems for each layer. We present a slope scaling procedure for multilayer network design problem to find good feasible solutions in reasonable time.
04:20 PM - 04:45 PM
Accelerating L-shaped decomposition algorithm for two-stage stochastic network design problems
Stochastic network design problems are relevant in various fields, ranging from logistics to telecommunication. However, obtaining optimal solution for such problems is extremely challenging, particularly in the case of large-scaled instances. In this presentation, we discuss several acceleration strategies that can be applied in the L-shaped decomposition method to efficiently solve such problems.
04:45 PM - 05:10 PM
Accelerating Benders decomposition for closed-loop supply chain network design
We study a closed-loop supply chain in the context of durable products with modular structures. To this end, a MIP model is presented based on a disassembly tree where the number of each sub-assembly depends on the quality status of returns. We present a Benders decomposition-based solution algorithm together with several algorithmic enhancements for this problem.