10h30 - 10h55
A two-stage robust approach for the reliable logistics network design problem
This paper examines a three-echelon logistics network in which all supply and transshipment nodes are subject
to disruptions. Uncertainty sets are employed to describe the concerned possible scenarios without depending
on probabilistic information. We adopt a two-stage robust optimization approach where location decisions are
made before and recourse decisions are made after disruptions being revealed. Three related two-stage robust
models are constructed, which are solved exactly by a column-and-constraint generation algorithm. Numerical
tests demonstrate that the proposed algorithm outperforms the Benders decomposition method in both solution
quality and computational time, and that the system’s reliability can be gradually improved with only a slight
increase in normal cost.
10h55 - 11h20
Branch-and-cut methods for the Network Design Problem with Vulnerability Constraints
The Network Design Problem with Vulnerability Constraints imposes resilience against failures and bounds on the lengths of each communication path. When solving the state-of-the-art formulations in CPLEX, we cannot solve most instances based on large-sized networks. Therefore, we propose branch-and-cut methods that greatly improve the efficiency of solving this problem.
11h20 - 11h45
Design of Green Food Systems under Nutritional Considerations
This research aims to propose an integrated network design problem for the global food system, incorporating production and consumption decisions within one common framework. Including sourcing, processing and transportation aspects, the developed model optimises both cost and environmental objectives and investigates possible trade-offs and shifts in environmental burdens.
11h45 - 12h10
A Benders based algorithm for the uncapacitated multicommodity network design problem
In this study, we present a novel exact algorithm for the uncapacitated multicommodity network design problem. Our algorithm combines the use of a modified Benders reformulation of the model, bound strengthening and heuristics to obtain primal bounds. We analyze the performance of the algorithm on benchmark instances and compare them with current solution methods.