Séminaires

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

Hybride : 13 Mai, 10h30 – 12h: https://uqam.zoom.us/j/88214941485

Pour participer en présentiel, veuillez réserver une place en contactant Janosch Ortmann.

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

Hybride : 13 Mai, 9h – 10h30: https://uqam.zoom.us/j/88214941485

Pour participer en présentiel, veuillez réserver une place en contactant Janosch Ortmann.

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

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

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.



Öykü Naz Attila: Mitigating Choice Model Ambiguity: The Case of Assortment Optimization

EN LIGNE: Jeudi 7 avril, à 11h30

Abstract: In this study, we propose a novel framework to tackle the ambiguity associated with a given set of predictive models in terms of their ability to yield optimal decisions. The ambiguity of interest here arises from the differences between estimated predictive models, which is a natural consequence of employing statistical estimation methods. These differences remain, even when predictive models are trained under the same training data and to the same level of accuracy. To combat the consequences of choice model ambiguity, we first provide a framework that utilizes metrics to identify predictive models that perform well in terms of their ability to induce better decisions. Secondly, we introduce stochastic and robust optimization problems that employ an uncertainty set structure to hedge the risk of using predictive models that perform relatively poorer. To further motivate and demonstrate the use of this framework, we provide a detailed implementation of the framework on assortment optimization problems, where the objective is to choose an optimal set of products to be offered to customers, such that the expected revenue generated from the total sales is maximized. Since these problems rely on the use of predictive models (i.e. choice models) that represent customer behavior, handling choice model ambiguity in such problems becomes a crucial task in order to obtain accurate and optimal decisions.

Öykü Naz Attila is a postdoctoral researcher at ESG-UQAM. Her research interests mainly involve mixed-integer programming, optimization models under uncertainty, and framework development for handling uncertainty in specific applied optimization problems.

Séminaire: JEUDI / THURSDAY

7 avril/April 2022, 11h30 -En ligne seulement – Ouvert à tous / Open to all


Hani Zbib. The Optimisation of Recyclable Waste Collection Services

Sustainably recycling and treating waste has gained a lot of traction in the context of circular economies, which consequently resulted in waste collection becoming more complex. This is mainly due to the many recycling-related technological features and configurations available on waste collection vehicles that can highly affect the efficiency of recyclable waste collection services. In this talk, I will present an overview of the technological features of collection vehicles that affect recyclable waste collection service, and how these features affect the design of waste management systems. I will also present how these features and systems can be modelled as rich variants of the capacitated arc routing problem (CARP) in the context of curbside waste collection. Finally, I will present an algorithm to solve the Commodity-Split Multi-Compartment CARP with compression factors and commodity-dependent compartment capacities

Lien ZOOM: https://uqam.zoom.us/j/84930961805

Gabriel Homsi. ROLLING HORIZON STRATEGIES FOR A DYNAMIC AND STOCHASTIC RIDE SHARING PROBLEM WITH REMATCHES. (22 avril 2021 à 11h00)

Gabriel Homsi: ROLLING HORIZON STRATEGIES FOR A DYNAMIC AND STOCHASTIC RIDE SHARING PROBLEM WITH REMATCHES.

10 mars 2021Mohammad Daneshvar. A 2stage Stochastic Humanitarian Relief Network Design Problem.

Seminar by Mohammad Daneshvar 10 mars 2021 (A 2stage Stochastic Humanitarian Relief Network Design Problem)

 Seminar: DYNAMIC, STOCHASTIC, AND COORDINATED OPTIMIZATION FOR SYNCHRO MODAL MATCHING PLATFORMS. (Pour participer au webinaire / To joint the Webinar: https://uqam.zoom.us/j/89667489443)

Dr Wenjing Guo, chercheure postdoctorale ESG

Seminar: Competition and Coordination in Organic Food Supply Chains.  11 février à 10:00 

Dr Nematollahi – Mohammadreza – Seminar 2021

Séminaires – 2020

2020-11-25 – David Escobar : Synchronization in Two-Echelon Distribution Systems: Models, Algorithms and Sensitivity Analyses

David Escobar

2020-10-27- Gita Taherkhani: Profit Maximizing Hub Location Problems

2020-06-03 – Janosch Ortmann:  Clustering methods for stochastic optimization

2019-12-04 – Marie-Pier Séguin: Risk evaluations of transportation corridors for humanitarian aid: The case of the World Food Programme based in Niger

2019-11-06 – Rosemarie Santa Gonzalez:Applying the Multiperiod Location Routing Problem to Mobile Clinic Deployment

2019-10-09 – Maria Camila Vasquez-Correa:On similarity measures for medical images registration

2019-09-11 – Charlotte Köhler: Dynamic flexible time windows pricing

2019-05-16 – Tone Lehrer: Shuttle-based storage and retrieval systems in Warehousing 4.0

2019-03-12 – Ana Maria Anaya-Arenas: Integrated planning for humanitarian and healthcare logistics

2019-02-19  – Ygal Bendavid L’IdO en logistique – Applications et implications

2019-01-22 – Teodor Gabriel Crainic : Recherche opérationnelle et applications au transport et à la logistique

2018-11-27 – Yasmina Maïzi: Simulation based decision making for health care operations management

2018-10-08 – Sanjay Dominik Jena : Optimisation d’assortiments guidée par les données

2018-09-18 – Walter Rei : Optimisation stochastique des systèmes de transport et logistique

2018-09-05 – Walid Klibi: Designing two-echelon networks under uncertainty

2018-10-18 – Szymon Albinski: Application of Operations Research and Big Data to New Mobility Concepts and the Stochastic VRPTW