4 présentations

• 
  15h30 - 15h55

  A metaheuristic solution approach for large-scale stochastic mixed integer non-linear optimization of mineral value chains

  • Christian Both, prés., COSMO Stochastic Mine Planning Laboratory, McGill University
  • Roussos Dimitrakopoulos, COSMO Stochastic Mine Planning Laboratory, Université McGill

  An adaptive neighborhood search is presented for the non-linear stochastic optimization of mineral value chains, which typically requires a very large number of integer and continuous variables. Solutions obtained by the metaheuristic are compared to conventional packages when being applied on a real-world mining complex.

  Keywords: metaheuristics; stochastic mixed integer programming, adaptive neighborhood search
• 
  15h55 - 16h20

  An infeasible start heuristic for the transit route network design problem

  • Nurit Oliker, prés., Postdoctoral fellow, Université de Montréal
  • Shlomo Bekhor, Professor, Faculty of Civil and Environmental Engineering Technion - Israel Institute of Technology Haifa 32000, Israel

  This study develops a heuristic model for the transit network design problem. The model includes a preliminary step of route set generation, followed by an iterative procedure that simultaneously selects the best routes and corresponding headways. Results show a significant reduction in the average travel time for a benchmark network.

  Keywords: public transportation ; transit network design ; heuristic
• 
  16h20 - 16h45

  Automatic combination of metaheuristic components

  • Victor Parada, prés., University of Santiago of Chile
  • Sergio Iturra, University of Santiago of Chile
  • Carlos Contreras-Bolton,

  The design of a heuristic algorithm to solve an optimization problem can also be seen as an optimization problem Such problem seeks to determine the best of the algorithms contained in the search space. The objective function corresponds to the computational performance of the algorithm measured in terms of computational time, complexity, number of instructions or number of elementary operations. The automatic design of algorithms has been explored for several combinatorial optimization problems. In this work, we extend this exploration towards the automatic design of metaheuristics to find solutions for the traveling salesman problem. The process is carried out with genetic programming. The resulting algorithms are combinations of well-known metaheuristics and in some cases present better computational performance than the existing algorithms for the set of selected test instances. Besides, from the algorithmic components selected it was possible to rediscover some of the existing metaheuristics.
• 
  16h45 - 17h10

  VNS for solving the location of Phasor Measurement Units (PMU) and Wide Area Measurement Systems (WAMS) in transmission networks.

  • Eglantine Camby, prés., Université Libre de Bruxelles
  • Marco Cruz, Laboratory of Telecommunications at Federal University of Espírito Santo
  • Helder Rocha, Laboratory of Telecommunications at Federal University of Espírito Santo
  • Marcia Paiva, Laboratory of Telecommunications at Federal University of Espírito Santo
  • Marcelo Segatto, Laboratory of Telecommunications at Federal University of Espírito Santo
  • Gilles Caporossi, HEC Montréal

  PMU were introduced in the 1990’s: they are located on buses to bring accurate information on the network while WAMS make the connection between them. The main disadvantage of PMU is their cost. Accordingly, locating PMU in a tramission network became an optimisation problem. Here, we propose new algorithm based on the Variable Neighbourhood Search approach.
  Phasor Measurement Unit (PMU), Wide Area Measurement Systems (WAMS), Variable Neighbourhood Search, Communication infrastructure.