15h30 - 15h55
Improving airline crew satisfaction by considering flight preferences in the crew pairing problem
The airline crew scheduling problem is studied by many researchers. Usually, the problem is divided in two steps : the crew pairing problem (CPP) and the crew rostering problems (CRP). While the goal of the CPP is to find feasible pairings at minimum cost, the CRP aims at finding a feasible schedule that satisfy as many employee preferences (preferred airlegs, vacations, etc.) as possible. The main challenge with this approach is that the pairings generated by the CPP may not be suitable for the objective of the CRP. For instance, typical solutions to the CPP contain very few pairings with multiple airlegs preferred by a single crew member, limiting the total number of preferences that can be granted.
In order to create pairings that are more compatible with the CRP, we propose a new mathematical formulation for the CPP that favors pairings containing multiple airlegs that are preferred by a single crew member. We show how such model can be solved with column generation, using shortest path problems with ressource constraints as subproblems. Finally, we present results showing the effectiveness of our method.
15h55 - 16h20
Integrated bus driver rostering and days off scheduling
We consider the problem of assigning duties and days off simultaneously to bus driver rosters in order to balance as much as possible the weekly working time among the rosters while satisfying various working rules concerning mostly the rest periods between two working days, and the number of days off per week. We model this problem as an integer program and we report computational results obtained on real-world instances.
16h20 - 16h45
The Container Scheduling and Cross-dock Door Selection Problem
In this talk, we introduce an integrated scheduling and selection problem that is motivated by a cross-docking application. The daily decisions of scheduling containers and selecting dock doors to unload these containers are carried out simultaneously. The objective is to minimize the total weighted tardiness cost resulting from scheduling containers plus the total labor cost resulting from selecting dock doors to unload containers. We introduce two integer programming models for static and dynamic environments. Computational experiments show that our new static model significantly outperforms the best existing one, and the dynamic one is able to solve real life instances optimally in a reasonable time.