3 présentations

• 
  10h30 - 10h55

  International Project Scheduling by Linear Programming

  • Alban Piveteau, prés., Polytechnique Montréal
  • Michel Gamache, GERAD - Polytechnique Montréal
  • Robert Pellerin, École Polytechnique de Montréal

  The aim of this presentation is to introduce a new scheduling problem fitted to schedule industrial projects realized in an international context. In particular, we will insert and present a logistic constraint to typical RCPSP problem.
  Next, we will focus on a new way to solve the NP-hard problem by using an iterative algorithm based on a linear program and a fictive lower bound in order to expedite the Branch & Bound procedure.

• 
  10h55 - 11h20

  An Implicit Model for Multi-Activity Shift Scheduling Problems

  • Sana Dahmen, prés., Université Laval et Cirrelt
  • Monia Rekik, Université Laval

  We present an implicit model for shift scheduling problems in multi-activity contexts where all employees are assumed to have the same qualifications. The scheduling environment considers multiple shift lengths and break-placement flexibility. The objective is to minimize workforce costs while satisfying the demand at each period of the planning horizon. Preliminary results will be presented.

• 
  11h20 - 11h45

  Bicriteria Unrelated-Parallel Machine Scheduling with Dual Resources

  • Rasaratnam Logendran, prés., Oregon State University
  • Yasaman Mehravaran, Oregon State University

  We focus on the problem of minimizing both the weighted completion time and weighted tardiness of an unrelated-parallel machine scheduling problem in the presence of dual resources. The problem is motivated by a real problem in the industry, wherein machines and manpower are the constrained resources with the latter being more constrained than the former. The setup times are sequence-dependent, multiple-skill levels exist for performing both the setup and run of a job depending upon its complexity. We present a model and a search algorithm for solving this problem and demonstrate their applicability using an example problem.