A note on 'Variable Neighborhood Search Based Algorithms for Crossdock Truck Assignment'

Some implementations of variable neighborhood search based algorithms were presented in \emph{C\'ecilia Daquin, Hamid Allaoui, Gilles Goncalves and Tient\'e Hsu, Variable neighborhood search based algorithms for crossdock truck assignment, RAIRO-Oper. Res., 55 (2021) 2291-2323}. This work is based on model in \emph{Zhaowei Miao, Andrew Lim, Hong Ma, Truck dock assignment problem with operational time constraint within crossdocks, European Journal of Operational Research 192 (1), 2009, 105-115 }m which has been proven to be incorrect. We reiterate and elaborate on the deficiencies in the latter and show that the authors in the former were already aware of the deficiencies in the latter and the proposed minor amendment does not overcome any of such deficiencies

A Neural Benders Decomposition for the Hub Location Routing Problem

In this study, we propose an imitation learning framework designed to enhance the Benders decomposition method. Our primary focus is addressing degeneracy in subproblems with multiple dual optima, among which Magnanti-Wong technique identifies the non-dominant solution. We develop two policies. In the first policy, we replicate the Magnanti-Wong method and learn from each iteration. In the second policy, our objective is to determine a trajectory that expedites the attainment of the final subproblem dual solution. We train and assess these two policies through extensive computational experiments on a network design problem with flow subproblem, confirming that the presence of such learned policies significantly enhances the efficiency of the decomposition process

Capacitated Hub Routing Problem in Hub-and-Feeder Network Design: Modeling and Solution Algorithm

International audienceIn this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein eachhub acts as a transshipment node for one directed route. The number of hubs lies between a minimum anda maximum and the hub-level network is a complete subgraph. The transshipment operations take place atthe hub nodes and flow transfer time from a hub-level transporter to a spoke-level vehicle influences spoketo-hub allocations. We propose a mathematical model and a branch-and-cut algorithm based on Bendersdecomposition to solve the problem. To accelerate convergence, our solution framework embeds an efficientheuristic producing high-quality solutions in short computation times. In addition, we show how symmetrycan be exploited to accelerate and improve the performance of our method

Capacitated Hub Routing Problem in Hub-and-Feeder Network Design: Modeling and Solution Algorithm

International audienceIn this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein eachhub acts as a transshipment node for one directed route. The number of hubs lies between a minimum anda maximum and the hub-level network is a complete subgraph. The transshipment operations take place atthe hub nodes and flow transfer time from a hub-level transporter to a spoke-level vehicle influences spoketo-hub allocations. We propose a mathematical model and a branch-and-cut algorithm based on Bendersdecomposition to solve the problem. To accelerate convergence, our solution framework embeds an efficientheuristic producing high-quality solutions in short computation times. In addition, we show how symmetrycan be exploited to accelerate and improve the performance of our method

Hub Location Models in Public Transport Planning

The dissertation deals with the application of Hub Location models in public transport planning. The author proposes new mathematical models along with different solution approaches to solve the instances. Moreover, a novel multi-period formulation is proposed as an extension to the general model. Due to its high complexity heuristic approaches are formulated to find a good solution within a reasonable amount of time