Michel Gamache

A Column Generation Approach for Large-Scale Aircrew Rostering Problems

This article describes a method for solving the crew rostering problem in air transportation. This problem consists of constructing personalized schedules that assign pairings, days off, and other activities to airline crew members. A generalized set partitioning model and a method using column generation have been used. This method has been adapted in a number of ways to take advantage of the nature of the problem and to accelerate solution. Numerical tests on problems from Air France have demonstrated that this method is capable of solving very large scale problems with thousands of constraints and hundreds of subproblems. The tests have also shown that these adaptations are capable of reducing solution time by a factor of about a thousand. Finally, results from this method are compared with those obtained with the method currently used at Air France.

A Method for Optimally Solving the Rostering Problem

This paper presents a prototype method for optimally solving the rostering problem, i.e., constructing work schedules for airline crew members. The main goal is to show the possibilities of solving the rostering problem using optimal methods. The prototype uses a column generation approach embedded in a branch and bound algorithm to solve the rostering problem. To the knowledge of the authors, this prototype is the first optimal method for solving the rostering problem.

A graph coloring model for a feasibility problem in monthly crew scheduling with preferential bidding

We consider a monthly crew scheduling problem with preferential bidding in the airline industry. We propose a new methodology based on a graph coloring model and a tabu search algorithm for determining if the problem contains at least one feasible solution. We then show how to combine the proposed approach with a heuristic sequential scheduling method that uses column generation and branch-and-bound techniques.

CREW SCHEDULING IN AIR TRANSPORTATION

This paper addresses some crew scheduling problems faced by airlines during both the planning and the operational phases. Given a flight schedule and a fleet assignment, the planning process consists first in solving a crew pairing problem for each fleet of aircraft and then in constructing a monthly work schedule for each individual crew member. At the operational level, some crew pairings and schedules must be modified in order to compensate for certain disruptions that occur during the operations. The operational crew scheduling problem involves making these modifications.

An enumeration algorithm for solving the fleet management problem in underground mines

This paper presents an enumeration algorithm based on dynamic programming for optimally solving the fleet management problem in underground mines. This problem consists of routing and scheduling bidirectional vehicles on a haulage network composed of one-lane bidirectional road segments. The method takes into account the displacement modes of the vehicles, either forward or in reverse, and makes sure that these vehicles move forward when they arrive at their service point. The method has been developed for the underground mine context, but it can be extended to the industrial environment.

A shortest-path algorithm for solving the fleet management problem in underground mines

Abstract This paper describes the problem of managing a fleet of load-haul-dump (LHD) vehicles in an underground mine. The problem consists of dispatching, routing and scheduling vehicles whenever they need to be assigned to a new task. The solution approach is based on a shortest-path algorithm. Each decision takes into account the current status of the mine, the current traffic on all single-lane bi-directional road segments of the haulage network and operational constraints such as the fact that, while LHD vehicles move in forward or reverse modes, their bucket must be in dumping/loading position at destination.

Mixed integer programming model for short term planning in open-pit mines

Abstract In this paper, a mixed integer programming model for solving the short term planning problem in surface mining is presented. This model will establish the sequence of mining for a period ranging from days to several months. This involves determining which blocks of the geological model will be extracted and in what order, indicating the movement of the shovels and meeting the production capacity of equipment. To reduce the computation time, four sets of strategies are proposed.

An Exact Solution Approach for the Preferential Bidding System Problem in the Airline Industry

This paper introduces the first exact approach for constructing aircrew member personalized monthly work schedules when a preferential bidding system (PBS) is used. With such a system, each employee bids for his/her preferred activities, yielding a bidding score for each feasible schedule. The PBS problem thus consists of assigning to each employee a schedule that maximizes his/her preferences, in order of seniority, while covering all crew pairings. The proposed exact solution approach relies on column generation, and when a tentative maximum score for a crew member is established, it explicitly enumerates for that employee all feasible schedules with that score. Tests on real-life cases show that this approach can substantially improve the quality of the solutions produced by the best known existing method in similar computational times.

A framework for realistic microscopic modelling of surface mining transportation systems

This article presents a recently developed realistic microscopic simulator for surface mining transportation systems called Surface Mining Transportation Simulator (SuMiTSim). In the road transport sector recent researches proved that for proper deployment of Intelligent Transportation Systems (ITS), the use of microscopic simulation models rather than the conventional macroscopic ones is critical. Microscopic simulators emulate realistically the dynamic traffic on a road network. A conceptual framework for the development of a surface mining micro-simulator is then proposed. The implementation of this framework led to SuMiTSim which is a robust tool for truck traffic analysis and control. Two case studies have been conducted. The results obtained from the first case study show clearly the benefits that can be derived when using SuMiTSim as a laboratory for more efficient haul roads design. The second finding concerns the integration of SuMiTSim as a proactive updater for real-time allocation. Other potential uses of SuMiTSim are highlighted, such as for sound environmental management through controlling fuel consumption and reducing truck bunching effects on mine networks.

Specification of an intelligent simulation-based real time control architecture: Application to truck control system

The paper presents an implemented architecture of an intelligent simulation-based real-time control (SRTC) system for industrial applications. The proposed SRTC uses a trajectory tracking strategy inspired from the model-based predictive control approach. Dynamic control law based on the closed-loop feedback correction is embedded. A computer implementation of this control scheme and experiments are conducted for real-time truck dispatching on a surface mine transportation system. Results showed the capability of the SRTC to generate efficient real-time truck dispatching orders at each 120s. Simulation results demonstrate that managing trucks with such dynamic control law improves productivity. This improvement is reached when the transportation system is under steady as well as transient states conditions. The proposed SRTC makes use of the intelligent metaheuristic optimization search even under tight timeliness constraints.