Seminars

To see the calendar of all CRI2GS seminars follow this link: CRI2GS calendar. All talks are taking place at UQAM unless otherwise indicated.

Nadia Tahmasbi (UQAM): Optimizing freight transport through intelligent match-making under uncertainty

Tuesday 26 March, 1pm – 2.30pm. DS-1525


Esteban Ogazón (Laval/CIRRELT/CRI2GS): Multi-period bin packing problem and effective constructive heuristics for corridor-based logistics capacity planning

Tuesday 23 January 2024, 10.30 – 12noon. DS-2950.

Francesco Contu (University of Cagliari) A Location-Network Design with Vehicle Selection in City Logistics

Thursday 9 November 2023, 1pm. -UQAM, Hubert-Aquin A-1875

Johannes Gückel – KU Eichstatt-Ingolstadt – RESOURCE ALLOCATION IN TWO-TIER LOGISTICS

Thursday 9 November 2023, 1pm. -UQAM, pavillon Hubert-Aquin A-1875

Franklin Djeumou Fomeni (UQAM): Multi-period bin packing problem and effective constructive heuristics for corridor-based logistics capacity planning

Hybrid talk, 13 May 2022, 10.30am – 12noon: https://uqam.zoom.us/j/88214941485

If you would like to participate in person, please contact Janosch Ortmann as places are limited.

Abstract: The bin packing problem is one of the most studied combinatorial optimization problems. This talk will present two recent bin packing problem settings with many practical applications, in particular in logistics capacity planning. Both problems explicitly consider, besides the classical bin-selection costs, the item and bin-specific item-to-bin assignment costs. These assignment costs depend not only on the physical, e.g., item and bin size, and economic, e.g., bin selection fixed cost and the cost of item “transport” by the bin, but also on the temporal attributes of items and bins, e.g., availability of regular bins for selection and utilization and of items to be assigned to such a regular bin. Special, item- specific in terms of size, spot-market bins may be used at higher cost for the items that one cannot fit into the selected bins. Single and a multi-period formulations are proposed, both aiming to minimize the total cost of the system computed as the sum of the fixed costs of the selected bins and the total item-to-bin assignment cost using regular and spot-market bins. The multi-period formulation optimizes the cost over all the time periods considered.

Franklin Djeumou Fomeni is currently an Assistant Professor in Operations Research at ESG-UQAM. He received a PhD in Management Sciences from Lancaster University in the UK, an MSc in Applied Mathematics from the University of the Witwatersrand in South Africa and a Postgraduate Diploma from the African Institute for Mathematical Science (AIMS South Africa. His research interests span the theory and the application of operations research methods to problems in transportations, logistics, production planning and sustainability. He has worked on projects from the European organization for the safety of air navigation (EUROCONTROL), as well as on projects from companies in the tea, sugar and mining industries.

Matthieu Gruson (UQAM): MODELLING AND SOLVING THE INTEGRATED THREE LEVEL LOT SIZING AND REPLENISHMENT PROBLEM

Hybrid talk, 13 May 2022, 9am – 10.30am: https://uqam.zoom.us/j/88214941485

If you would like to participate in person, please contact Janosch Ortmann as places are limited.

Abstract: Over the last decades, the value of integrating operational decisions has become obvious to manufacturing companies. The main reason behind this integration, whether it is within a company or across a supply chain, can be easily explained by the potential benefits, such as cost reduction, increased flexibility or a higher customer service level. Several studies have built on this observation and successfully proposed mathematical models that take into account the integration of operational decisions, such as the production and distribution decisions. Despite these success stories, the integration of operational decisions at a broader level is still not fully exploited. The objective of the work presented in this seminar is to use operations research techniques to optimize the integration of operational decisions within a supply chain with three levels and a distribution structure. The first, second and third level comprise a unique production plant, several warehouses and several retailers, respectively. The problem under study is therefore an integrated three-level lot sizing and replenishment problem (3LSPD). The main contributions lie in the mathematical models proposed along with the efficient algorithms developed to solve different versions of the problem, all of which integrate the production and replenishment decisions, while minimizing the operational costs across the supply chain.

Matthieu Gruson is a professor at ESG-UQAM in the analytics, operations and information technology department. His research interests lie in the integration of production decisions along with other operational decisions of manufacturing companies. It involves modelling such problems, and designing efficient methods to solve them, use operations research tools.

Mohammad Daneshvar – PhD Candidate, UQAM

Online, 25 Avril 2022, 11h00 – 12h00: https://uqam.zoom.us/j/82752761239

Title: Handling ambiguity in a humanitarian relief network design problem

Abstract: After a natural disaster, a high level of uncertainty exists concerning the state of the region and the severity of the crisis among the affected population. To plan the humanitarian relief operations after a natural disaster, decision-makers receive estimations of the uncertain parameters that are produced using multiple data sources. The data sources could be surveys, satellite imagery, governmental reports, or media. However, the obtained estimates may have important discrepancies, directly leading to ambiguity being present in the informational context in which the planning process of humanitarian relief operations occurs. In this seminar, I will present our ongoing work to study different approaches to deal with the inconsistent estimates obtained from multiple data sources in modeling the Humanitarian Relief Network (HRN) design problem after a natural disaster. Specifically, we study the problem of designing an HRN that is used to perform the storage and distribution of critical supplies among an affected population over a given time horizon. Multiple two-stage stochastic models are developed to formulate the problem that explicitly considers the uncertainty that affects both the needs of the population, as well as the transportation and storage capacities of the network. The models are then used to solve a series of instances obtained using multiple scenario sets to study the effects that different ambiguity patterns have on the obtained solutions of the proposed models.

Mohammad Daneshvar is a Ph.D. candidate at ESG-UQAM working on the Humanitarian Relief Network Design problem. He has an M.Sc. in Decision Science and a B.Sc. in Computer Science from the University of Tehran. His research interests include optimization models under uncertainty, network science, and data mining.