3 Presentations

• 
  03:30 PM - 03:55 PM

  Improving the decision-making process by considering supply uncertainty – a case study in the forest value chain

  • Vanessa Simard, presenter, Université Laval

  Planning decisions are generally subject to some level of uncertainty. In forestry, data describing the resources available have a major impact on operations performance and productivity. This paper aims to present a method to improve decision-making in the forest supply chain by taking supply uncertainty into account using the results of data quality assessments. The case study describes the operations planning process of a Canadian forest products company dealing with an uncertain volume of wood supply. Three approaches to constructing probability distributions based on data quality are tested. Each approach offers a different level of precision: (1) a frequency distribution of accuracy, (2) a normal distribution based on average accuracy, and (3) a normal distribution based on data quality classification. Using stochastic programming to plan transport and production shows that lower costs can be achieved with a general characterisation of the data accuracy. Not considering uncertainty when planning operations leads to a significant replanning transportation cost. Using classes of data quality to include uncertainty in operations planning contributes to reducing the transportation cost from $15.90/m3 down to $15.32/m3 representing 3.6%.
• 
  03:55 PM - 04:20 PM

  Optimizing truck platooning transportation planning: an application to forestry products supply chains

  • Saba Gazran, presenter, École de technologie supérieure
  • Tasseda Boukherroub, École de technologie supérieure
  • Mikael Rönnqvist, Université Laval
  • Marc Paquet, École de technologie supérieure

  The Fourth Industrial Revolution offers new opportunities for improving the efficiency and agility of supply chain operations such as transportation. This study explores the impact of integrating truck platooning technology in forestry products supply networks. Companies need to know how and where to use truck platooning in transportation networks to get optimum benefits from truck platooning in supply chains. To this end, a Mixed-Integer Linear Programming (MILP) model was developed. Decisions to be made include the selection of the potential terminal locations, the number of ordinary and platooning trucks needed in the transportation network, the origin and destination of products, and their flow in direct and backhaul routes. The objective is to minimize the overall transportation cost including terminal location costs, fixed costs for ordinary and platoon trucks, fuel, and driver costs. The results show that the potential savings of combining the two types of trucks are in the range of 1%–12% in the scenarios in which truck platooning transportation is allowed only between terminal and mill nodes. This savings could reach more than 20% when the truck platoons are allowed to visit forest areas, depending on how many forest areas are visited. The number of drivers can be reduced by 3% to more than 30%. In addition, using truck platooning and backhauling together could reduce fuel consumption by 15.6% on average.
• 
  04:20 PM - 04:45 PM

  Resource allocation in a collaborative reforestation value chain: Optimisation with multi-objective models

  • Mahtabalsadat Mousavijad, presenter,
  • Lehoux Nadia,
  • Luc LeBel,
  • Caroline Cloutier,

  The reforestation value chain depends on the selection of qualified seeds supplied from various sources to ensure the successful growth, as each reforestation site has particular ecological parameters. The reforestation process usually involves many partners from different organisations, increasing the complexity of seed allocation. This research addresses seed allocation in a collaborative, make-to-order reforestation value chain. Using multiobjective optimisation models and considering different degrees of collaboration, it aims to find the most compatible seeds for each reforestation site so as to favour regeneration success. As a case study, the models are applied to the Quebec reforestation value chain which manages over 1450 seed lots and an annual production of 130 million seedlings. The process must consider two groups of partners: a seed center, and 18 nurseries. The lexicographic method is used to solve the models. Results show that an array of optimal solutions favouring reforestation success are possible by considering the main objective in each model. The second objective, integrating partners’ objectives separately, modifies the initial solution significantly. Furthermore, when the objectives of both groups of partners are considered simultaneously, the proposed allocation differs depending on their priority, while the reforestation success objective does not deteriorate. The proposed set of models provide decision makers with a means to rapidly find a suitable seed allocation plan that favours reforestation success while considering partners satisfaction and existing bottlenecks in the value chain. This article contributes to the field by providing a sustainable seed allocation model favouring reforestation success covering the three pillars of sustainability.
  Keywords: Resource allocation, Seed allocation, Reforestation value chain, Collaboration, Multi-objective model, Priority of objectives