4 présentations

• 
  10h30 - 10h55

  Selling and Renting Mechatronics: Digitally Controlled Physical Goods

  • Xianfeng Meng, prés., Smith School of Business, Queen's University
  • Guang Li, Smith School of Business, Queen's University
  • Anton Ovchinnikov, Smith School of Business, Queen's University

  Firms that sell digital goods routinely utilize free-premium-upgrade business models for product differentiation: when you download an app, you can try a free version first, then pay to unlock permanent premium functionality and rent additional temporary functionality. Recent technological advances allow physical goods firms to do the same: they can create products which have identical hardware that can be digitally controlled to allow for similar differentiation. In this paper, we present a stylized model to explore when physical goods firms (automakers, appliance manufacturers, etc.) should adopt such digitally-enabled product differentiation as opposed to the traditional product line design with high- and low-end products.
• 
  10h55 - 11h20

  Multi-Vendor, Multi-Buyer Supply Chain Optimization

  • Ibrahim Najum, prés., Université de Moncton
  • Nabil Nahas , Université de Moncton
  • Mohammed Abouheaf , College of Technology, Architecture & Applied Engineering, Bowling Green State University Bowling Green, 43402, OH, USA

  This article investigates inventory management coordination within a two-echelon multi-vendor multi-buyer supply chain, with the objective of minimizing total cost, consisting of set-up, holding, ordering, and transportation costs. Two coordination policies are proposed. In the first policy, each vendor produces a lot and delivers to all customers with delivery sizes proportional to their annual demand; in the second policy, the vendor ships a delivery to the buyer only when the previously sent batch is finished. A nonlinear programming model is developed for each policy to minimize the total cost, and a third integrated model combining both policies is also proposed.
  Numerical examples showed that the developed models effectively reduce the total cost of the supply chain and emphasize the benefits of integrating the two policies into a single model. Firms can adopt these policies to determine the optimal production and delivery quantities for their customers. By incorporating the unique characteristics of various suppliers, these models enhance decision-making accuracy and efficiency in inventory management. The integrated model offers a valuable contribution to supply chain management literature and has significant potential to impact supply chain management practices.
• 
  11h20 - 11h45

  Multi-objective Metaheuristic for a Rich Dynamic Berth Allocation Problem

  • Letícia Caldas, prés., PUC-Rio
  • Rafael Martinelli, Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)
  • Michel Gamache, Polytechnique Montréal

  Berths are scarce resources in port operations. Optimizing the use of this resource is a determining factor in handling the growing volume of bulk transportation. In the literature, the static berth allocation problem aims to optimally schedule and allocate ships, available at the beginning of the planning horizon, to port terminal positions. In contrast, in the dynamic berth allocation problem (DBAP), the vessels arrive during the planning horizon. To solve the problem, we propose a metaheuristic approach, based on the Iterated Local Search, for an extension of DBAP with constraints of a practical application in bulk ports. We consider a discrete case with a finite set of berthing locations and fixed length. The metaheuristic considers multiple objectives, such as minimizing queue time and makespan. To consider additional realistic restrictions, since each ship services one or more demands, we consider due dates, and, given contractual reasons, these demands must reach their destination in a specific period. Ship size constraints are also considered, limiting the berths in which ships can be moored. Experimental results prove the efficiency of the approach, comparing with instances in the literature and cases based on real-world data.
• 
  11h45 - 12h10

  Gateway Evaluation for Purolator International

  • Soltani Narges, prés.,
  • Hassini Elkafi,

  The transportation of goods is an important component of Canada's economy, and the industry is worth billions of dollars. It has an inclusive effect on other organizations. Making sound routing decisions and consolidating gateways whenever possible is crucial in an industry where profit margins are already low. This is especially critical for Canadian-based companies engaged in cross-border operations with the US, where the competition is more intense. The purpose of this paper is to assess Purolator International's northbound transportation network from the United States to Canada. Our approach involves using data envelopment analysis in conjunction with a multi-objective programming approach. The goal is to identify efficient patterns for allocating gateways to customers as well as maximizing gateways efficiency scores which are measured by the data envelopment analysis for selected gateways. We calculate gateway efficiencies based on multiple measures such as shipping volumes, the distance between gateways and customers, and the number of trucks to be dispatched from gateways to destinations across Canada. The efficient patterns also consider these measures in finding a cost-effective allocation. Using gateway efficiency can serve as a criterion that decision-makers consider when selecting the optimal locations for gateways. The periodic network re-evaluations can contribute to maintaining an optimal transportation network and help decision-makers to ensure that the network remains efficient and effective over time.