Formulations PLNE pour l'ordonnancement des chaînes sur une machine

National audienceLe problème considéré traite de l'ordonnancement de tâches par des radars aéroportés. Pour ce problème nous proposons deux programmes linéaires en nombres entiers

Tutorial: Modern Branch-and-Cut-and-Price for Vehicle Routing Problems Plan of the talk

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BaPCod - a generic branch-and-price code

This document presents a user guide for BaPCod version 0.63, a C++ library implementing a generic branch-cut-and-price solver. We give guidelines for installing BaPCod, using its modelling language, BaPCod parameterization, retrieving BaPCod statistics, and understanding BaP-Cod output. We also present the VRPSolver extension of BaPCod which allows one to model and efficiently solve a large number of vehicle routing and related problems

A Bucket Graph Based Labelling Algorithm for Vehicle Routing

International audienceWe consider the Shortest Path Problem with Resource Constraints (SPPRC) arising as a subproblem in state-of-the-art Branch-Cut-and-Price algorithms for vehicle routing problems. We propose a variant of the bi-directional label correcting algorithm in which the labels are stored and extended according to the so-called bucket graph. Such organization of labels helps to decrease significantly the number of dominance checks and the running time of the algorithm. We also show how the forward/backward route symmetry can be exploited and how to eliminate arcs from the bucket graph using reduced costs. The proposed algorithm can be especially beneficial for vehicle routing instances with large vehicle capacity and/or with time window constraints. Computational experiments were performed on instances from the distance constrained vehicle routing problem, including multi-depot and site-dependent variants, on the vehicle routing problem with time windows, and on the "nightmare" instances of the heterogeneous fleet vehicle routing problem. Significant improvements over the best algorithms in the literature were achieved and many instances could be solved for the first time

Improved Branch-Cut-and-Price algorithm for the Heterogeneous Vehicle Routing Problem

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Solving Bin Packing Problems Using VRPSolver Models

International audienceWe propose branch-cut-and-price algorithms for the classic bin packing problem and also for the following related problems: vector packing, variable sized bin packing and variable sized bin packing with optional items. The algorithms are defined as models for VRPSolver, a generic solver for vehicle routing problems. In that way, a simple parameterization enables the use of several branch-cut-and-price advanced elements: automatic stabilization by smoothing, limited-memory rank-1 cuts, enumeration, hierarchical strong branching and limited discrepancy search diving heuristics. As an original theoretical contribution, we prove that the branching over accumulated resource consumption (Gélinas et al. 1995), that does not increase the difficulty of the pricing subproblem, is sufficient for those bin packing models. Extensive computational results on instances from the literature show that the VRPSolver models have a performance that is very robust over all those problems, being often superior to the existing exact algorithms on the hardest instances. Several instances could be solved to optimality for the first time

A Branch-Cut-and-Price Algorithm for the Location-Routing Problem

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Solving the robust CVRP under demand uncertainty

International audienceIn this paper, we propose a Branch-Cut-and-price algorithm for the robust counterpart of the classical Capacitated Vehicle Routing Problem (CVRP). The deterministic version of this problem consists of finding a set of vehicle routes to serve a given set of customers with associated demands such that the sum of demands served by each vehicle does not exceed its capacity, and each customer is served exactly once. The total travel cost, given by the sum of distances traversed by all vehicles must be minimized. Here, only customer demands are assumed to be uncertain. We consider two types of uncertainty sets for the vector of customer demands: the classical budget polytope introduced by Bertsimas and Sim (2003), and a partitioned budget polytope, proposed by Gounaris et al (2013) for the CVRP with uncertain demands. The method proposed in this paper uses a set partitioning formulation to solve the problem, where each binary variable determines whether a given route is included or not in the solution. It considers only the routes that satisfy the capacity constraints for all possible demand vectors allowed by the uncertainty polytope. The linear relaxation for this formulation is solved by column generation, where the pricing subproblem is decomposed into a small number of deterministic subproblems with modified demand vectors. This reformulation allows the use of state-of-the-art techniques such as ng-routes, rank-1 cuts, specialized labeling algorithms, fixing by reduced costs and route enumeration. As a result, we were able to solve all 47 open instances proposed by Gounaris et al (2013), the largest one having 150 customers

A branch-cut-and-price approach for the single-trip and multi-trip two-echelon vehicle routing problem with time windows

The paper studies the two-echelon capacitated vehicle routing problem with time windows, in which delivery of freight from depots to customers is performed using intermediate facilities called satellites. We consider the variant of the problem with precedence constraints for unloading and loading freight at satellites. This variant allows for storage and consolidation of freight at satellites. Thus, the total transportation cost may decrease in comparison with the alternative variant with exact freight synchronization at satellites. We suggest a mixed integer programming formulation for the problem with an exponential number of route variables and an exponential number of precedence constraints which link first-echelon and second-echelon routes. Routes at the second echelon connecting satellites and clients may consist of multiple trips and visit several satellites. A branch-cut-and-price algorithm is proposed to solve efficiently the problem. This is the first exact algorithm in the literature for the multi-trip variant of the problem. We also present a post-processing procedure to check whether the solution can be transformed to avoid freight consolidation and storage without increasing its transportation cost. Our algorithm significantly outperforms another recent one for the single-trip variant of the problem. We also show that all single-trip literature instances solved to optimality admit optimal solutions of the same cost for both variants of the problem either with precedence constraints or with exact synchronization constraints

A branch-cut-and-price approach for the single-trip and multi-trip two-echelon vehicle routing problem with time windows

International audienceThe paper studies the two-echelon capacitated vehicle routing problem with time windows, in which delivery of freight from depots to customers is performed using intermediate facilities called satellites. We consider the variant of the problem with precedence constraints for unloading and loading freight at satellites. In this variant allows for storage and consolidation of freight at satellites. Thus, the total transportation cost may decrease in comparison with the alternative variant with exact freight synchronization at satellites. We suggest a mixed integer programming formulation for the problem with an exponential number of route variables and an exponential number of precedence constraints which link first-echelon and second-echelon routes. Routes at the second echelon connecting satellites and clients may consist of multiple trips and visit several satellites. A branch-cut-and-price algorithm is proposed to solve efficiently the problem. This is the first exact algorithm in the literature for the multi-trip variant of the problem. We also present a post-processing procedure to check whether the solution can be transformed to avoid freight consolidation and storage without increasing its transportation cost. It is shown that all single-trip literature instances solved to optimality admit optimal solutions of the same cost for both variants of the problem either with precedence constraints or with exact synchronization constraints. Experimental results reveal that our algorithm can be used to solve these instances significantly faster than another recent approach proposed in the literature