Jean-Marc Rousseau

A parallel route building algorithm for the vehicle routing and scheduling problem with time windows

This paper describes an insertion algorithm for the Vehicle Routing and Scheduling Problem with Time Windows (VRSPTW). This algorithm builds routes in parallel and uses a generalized regret measure over all unrouted customers in order to select the next candidate for insertion. Numerical results on the standard set of problems of Solomon are reported as well as comparisons with his sequential algorithm (Solomon, 1987).

The Vehicle Routing Problem with Time Windows Part I: Tabu Search

This paper describes a tabu search heuristic for the vehicle routing problem with time windows. The tabu search is based on specialized local search heuristics that maintain the feasibility of the solution at all time. Computational results on a standard set of test problems are reported, as well as comparisons with other heuristics.

Multicommodity, multimode freight transportation: A general modeling and algorithmic framework for the service network design problem

We examine the freight transportation problem which occurs when the same authority controls and plans both the supply of transportation services (modes, routes, frequencies for the services and classification, consolidation, transfer policies for terminals) and the routing of freight. We present a general modeling framework, based on a network optimization model, which may be used to assist and enhance the tactical and strategic planning process for such a system. The problem is solved by means of an algorithm, described in some detail, based on decomposition and column generation principles. We also present detailed results on the behaviour and performance of the algorithm, as observed during experimentation with a specific rail application.

A Tactical Planning Model for Rail Freight Transportation

This paper examines the problems of routing freight traffic, scheduling train services and allocating classification work between yards on a rail network. It describes a general optimization model which takes into account the interactions between these activities and develops global strategies for their management over a medium term planning horizon. A heuristic algorithm developed to solve this nonlinear, mixed-integer multicommodity flow problem is also presented with some computational results based on an example at the Canadian National Railroads.

A parallel implementation of the tabu search heuristic for vehicle routing problems with time window constraints

Abstract This paper describes a parallel Tabu search heuristic for the Vehicle Routing Problem with Time Windows. The parallel algorithm is synchronous and runs on a Multiple-Instruction Multiple-Data computer architecture. Parallelism is exploited by considering many different neighborhoods of the current solution, and by applying many modifications at once to the current solution. Computational results are reported on a standard set of test problems.

An Exact Constraint Logic Programming Algorithm for the Traveling Salesman Problem with Time Windows

This paper presents a constraint logic programming model for the traveling salesman problem with time windows which yields an exact branch-and-bound optimization algorithm without any restrictive assumption on the time windows. Unlike dynamic programmi ng approaches whose performance relies heavily on the degree of discretization applied to the data, our algorithm does not suffer from such space-complexity issues. The data-driven mechanism at its core more fully exploits pruning rules developed in opera tions research by using them not only a priori but also dynamically during the search. Computational results are reported and comparisons are made with both exact and heuristic algorithms. On Solomons well-known test bed, our algorithm is instrumental in achieving new best solutions for some of the problems in set RC2 and strengthens the presumption of optimality for the best known solutions to the problems in set C2.m

A Tabu Search Heuristic for the Vehicle Routing Problem with Backhauls and Time Windows

This article describes a tabu search heuristic for the vehicle routing problem with backhauls and time windows. In this problem, the set of customers is partitioned into two subsets: linehaul customers where a given quantity of goods is delivered from a central depot, and backhaul customers where a given quantity of goods is collected and transported to the depot. Mixed routes with both linehaul and backhaul customers are constructed. A variant of this problem is examined where linehauls must precede bachhauls on each route. Furthermore, the time of beginning of service at each customer location must occur within a particular time interval. Computational results are reported on a standard set of test problems, and comparisons are made with other heuristic approaches and with optimal solutions.

Bus Driver Scheduling — An Overview

In this paper, presented at the sixth International Workshop on Computer-Aided Transit Scheduling, the problem of bus driver scheduling is introduced, and some of the constraints and conditions existing in different user environments are presented. The way in which such conditions may affect solution methods is discussed.

A computer assistant for vehicle dispatching with learning capabilities

In this paper, we describe an expert consulting system for a dispatcher working in a courier service company. The system integrates interactive-graphic features and a learning module to support the dispatcher in his(her) task, and to suggest appropriate decisions when new requests come in. An experiment with a professional dispatcher is also reported.

The Column Generation Principle And The Airline Crew Scheduling Problem

AbstractThe generation and selection of a good set of pairings is a complex, costly and very central part of the airline crew scheduling process. We propose a column-generating type algorithm which, based on reduced costs manipulations, finds such a good set of pairings, namely the set containing the optimal solution to the linear relaxation of the set covering formulation of the problem.