4 Presentations

• 
  11:00 AM - 11:25 AM

  The Modified Vogel Method applied to Unbalanced Transportation Problem

  • Dalia Almaatani, Laurentian University
  • Salimata G. Diagne, Université Cheikh Anta Diop
  • Youssou Gningue, Laurentian University
  • Matthias P. Takouda, presenter, Laurentian University

  Unbalanced Transportation Problems are balanced by adding of dummy sources or destinations with big-M as related unit transportation costs. This makes it difficult to use a classic Vogel Approximation Method to obtain initial solution for the problem. We show the Modified Vogel Method overcomes these difficulties.

• 
  11:25 AM - 11:50 AM

  Reliability Model for Transportation Procurement Auctions

  • Hichem Klabi, presenter, Université Laval
  • Monia Rekik, Université Laval
  • Sehl Mellouli, Université Laval

  We consider a transportation procurement auction where winning bids are selected based on ask-prices and carriers reliability. The proposed model estimates reliability by combining internal (direct reliability and difference in beliefs) and external (indirect reliability) factors. Difference in beliefs represents the difference that exists between carrier bid-price and shipper beliefs.

• 
  11:50 AM - 12:15 PM

  Reputation-Based Winner Determination Problem in Centralized Transportation Procurement Auctions

  • Intissar Ben Othmane, presenter, Université Laval
  • Monia Rekik, Université Laval
  • Sehl Mellouli, Université Laval

  We consider a centralized procurement auction in which a set of shippers run together a unique auction. The objective is to determine winning bids knowing that: (1) a bid may include shipping contracts requested by different shippers and (2) a carrier reputation may differ from one shipper to another.

• 
  12:15 PM - 12:40 PM

  Investigating the Different Aspects of Information Sharing and Network Barrier on Disaster Relief Operations using ArcGIS and AIMMS

  • Ali Ahmed, presenter, Concordia University

  Purpose - explore the pros and cons of using modern GIS technology with over the top logistical optimization model and solution heuristics. Design/methodology/approach - Based on network design problems literature the adopted model is made of three steps: 1) Demand forecasting based on three scenarios (high, medium, and low impact probabilities). 2) locating warehouses and allocating impacted population 3) finding the best routes from the located warehouses to the impacted populations of each district. The case study is solved using exact and heuristics algorithms using AIMMS and arcGIS (respectively). Findings - Optimization heuristics used by the GIS software tested, arcGIS, are close to the optimal solutions provided by exact solution algorithms. Time and learning curve concerns have been raised. Practical implications - When choosing the right software to solve a network design problem, logisticians should take into consideration the use of GIS over the counter network design problem solvers, which provide satisfactory optimum solutions. As well as it has other benefits which are elaborated on in this research.Originality/value - The models are solved using two solution methods: exact algorithms (AIMMS software) and heuristics algorithms (arcGIS software). This adds to the credibility of using over the counter solutions pre-packed with multi-disciplinary GIS solutions. The power of GIS and open source data (network details, population, and geographic details) makes the model recreatable anywhere in the world.