10h30 - 10h55
Picker routing problem in mixed-shelves warehouses with multiple-blocks
We tackle the picker routing problem in mixed shelves warehouses. It is characterized by an order picker that starts from a central depot, walks through picking and cross-aisles to pick the items of her/his picklist, and comes back to the depot. Due to the mixed-shelves storage policy, each item is available on multiple shelves. The objective of the problem is to select the locations (shelves) from where to pick each item of the picklist and design the tour that visits the selected locations. To solve the problem, we propose a Logic-Based Benders Decomposition that selects the locations in the master problem and designs the tours that visits the selected locations in the subproblem.
10h55 - 11h20
A Systematic Literature Review on Logistics in Remote Regions
Food insecurity is a major concern in remote areas for many populations, including Northern Canada. For instance, in 2018, 57% of the Nunavut territory was food insecure, which is four times more than rest of the Canada (12.7%). This can partly be explained by the difficulty of access and the long distances for food suppliers. Moreover, the Northern Regions of Canada are rural territories with extreme climate, dispersed populations, poor living conditions and poor infrastructure. Such reality translates into high transportation costs, high costs of end products, and lastly, in food insecurity. We performed a systematic literature review that accounts for the current evidence-based research in OR/MS field for network design applications and product distribution in hard-to-reach regions. Three databases were used and over 3000 results were filtered. Finally, 100 papers were selected and analyzed. This talk presents the first results of our analysis, identifying the main characteristics of remote supply chain networks, the state-of-the-art optimization models, and the best practices regarding logistic optimization in remote areas. We will present research perspectives to identify contributions that can actually support decision-makers in the context of remote regions of Northern Canada and contribute to the national objective of food security.
11h20 - 11h45
Facility Location with Modular Capacity Under Demand Uncertainty: An Industrial Case Study
Facility location problem is a key element in location science analysis. The aim is to determine the number and location of facilities required to fulfill the demand of a set of customers at the minimal total cost. We address a facility location problem under modular capacity for Hydro-Quebec, a public service provider, to locate their service centers and capacities to satisfy the municipalities' demand. Considering the uncertainties in the demand, we formulate the problem in a two-stage stochastic setting. The location (i.e., strategic) decisions are static, whereas the capacities and transportation (i.e., tactic) decisions are adaptive. We suggest sample average approximation as a solution technique to solve a given case study. We presented the result in various data visualization forms to provide better insights of the uncertain demand impact on the logistics network.