
Including an Industrial Optimization Day
HEC Montréal, May 7 - 9, 2012
JOPT2012
HEC Montréal, 7 — 9 May 2012

MB2 Tournées de véhicules 1 / Vehicle Routing 1
May 7, 2012 10:30 AM – 12:10 PM
Location: KPMG
Chaired by Jean-François Cordeau
4 Presentations
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10:30 AM - 10:55 AM
A Modular Heuristic Algorithm for Bi-Criteria Multi-Depot and Periodic Vehicle Routing Problems
We propose a heuristic epsilon-constraint method to efficiently tackle three vehicle routing problems, i.e., multi-depot VRP, periodic VRP and multi-depot periodic VRP with capacitated vehicles and constrained route duration. In each of these problems, two contradicting objectives, i.e., total number of used vehicles and total traveled distance, are to be simultaneously minimized.
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10:55 AM - 11:20 AM
An Integrative Cooperative Search for a Bi-Criteria Multi-Depot Periodic Vehicle Routing Problem
We design an integrative cooperative search framework to solve a vehicle routing problem characterized by the presence of a homogeneous fleet of vehicles, multiple depots, multiple periods and two kinds of practical constraints, i.e., vehicle capacity and route duration constraints. The goal is to simultaneously optimize two conflicting objectives, i.e., total number of used vehicles and total traveled distance.
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11:20 AM - 11:45 AM
An Exact Algorithm for the Two-Dimensional Orthogonal Packing Problem with Unloading Constraints
We consider a packing problem found in the delivery industry, where it must be determined if a set of rectangular items can be loaded in a truck so that the items of each customer are directly reachable at the time of delivery (i.e., without moving any other item).
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11:45 AM - 12:10 PM
A Column Generation Algorithm for Multi-Depot Vehicle Routing Problem with Inter-Depot Routes
We propose a column generation algorithm to solve the multi-depot vehicle routing problem with inter-depot routes. We model it as a set-covering problem with an additional constraint and design two pricing subproblems to generate the variables. We embed the column generation algorithm in a branch-and-bound algorithm and conduct computational experiments.