{"id":109,"date":"2019-08-23T15:07:43","date_gmt":"2019-08-23T13:07:43","guid":{"rendered":"http:\/\/hec-cloud59.segi.ulg.ac.be\/~quantom\/?page_id=109"},"modified":"2026-05-05T13:55:51","modified_gmt":"2026-05-05T11:55:51","slug":"some-projects","status":"publish","type":"page","link":"https:\/\/www.quantom.hec.uliege.be\/index.php\/some-projects\/","title":{"rendered":"Some projects"},"content":{"rendered":"

<\/i><\/i><\/span>Applied\/Integration contribution<\/span><\/a><\/h4><\/div>
\n

LaaS \u00a0(2025 \u2013 2028)<\/strong><\/em><\/p>\n

Title: Enhancing the logistics of bidirectional flows in a laundry service company<\/p>\n

Abstract: The LaaS (Laundry as a Service) project aims to create an on-demand laundry service for individuals with a 72-hour turnaround from collection to delivery. Through a monthly subscription model, it enables the laundry service provider to expand into the B2C market. However, this approach results in a significant increase in collection and delivery points, as well as in the volume of laundry to process. Consequently, a major challenge lies in managing an optimized bidirectional logistics network to maintain operational efficiency. To address this challenge, the University of Li\u00e8ge (ULi\u00e8ge) contributes its expertise by developing logistical models that support the implementation of an efficient bidirectional supply chain.<\/p>\n

Funding: C-9095 (R\u00e9gion wallonne, P\u00f4le Logistics in Wallonia, P\u00f4le Mecatech)
\nPartner(s): Cool-Concept, Corematic, UCLouvain, ULi\u00e8ge.
\nProject leader(s): LIMBOURG, Sabine
\nResearcher(s): AGUAYO QUINTANA, Cristian, MOONEN, Charlotte<\/em><\/p>\n

E<\/b><\/span><\/em>COSOURCE (2024 – 2026)<\/b><\/span><\/em><\/p>\n

Title<\/span>\u00a0:<\/span> Web platform for supporting due diligence and deforestation analysis<\/span>with s<\/span>implified EUDR compliance<\/span><\/p>\n

Abstract:\u00a0<\/span>The <\/span>EcoSource<\/span> project aims to develop digital tools to support the implementation of the new European Union regulation on combating imported deforestation (EUDR) for European companies importing wood, cocoa, coffee, rubber, and palm oil. <\/span>These new regulations impose two new requirements on importers of these products: (i) <\/span>Conduct due diligence, i.e., <\/span>analyze<\/span> the risks of illegality and\/or human rights violations within their supply chain, all the way back to the original producer. (ii) <\/span>Conduct an analysis of the deforestation potential of the production areas of origin from which the imported product comes. <\/span>In order to<\/span> offer a solution tailored to the needs of European importers, <\/span>BFConsult<\/span>, <\/span>Deuse<\/span>, HEC-Li\u00e8ge, and <\/span>UCLouvain<\/span> have formed a consortium with the aim of developing <\/span>EcoSource<\/span>, a digital tool for companies importing these commodities. This tool aims to meet <\/span>all of<\/span> these requirements and has strong potential for commercialization.<\/span><\/p>\n

Partner(s) : BFConsult SRL, Deuse SRL<\/em>
Research center(s):\u00a0 QuantOM et CES de l’Universit\u00e9 de Li\u00e8ge et Earth and Life Institute (ELI) et Geomatics Research Lab de l’Universit\u00e9 Catholique de Louvain<\/em>
\nProject leader(s): Professors C\u00e9lia Paquay, Thierry Pironet, Virgine Xhauflaire<\/em>
\nResearcher(s): Antoine Gavroye (May 2024 – March 2025), Isaline Thirion Marc (2025 – present)<\/em><\/p>\n

COPS<\/span> (<\/span>2020 <\/span>\u2013<\/span> 2024<\/span>)<\/span><\/em><\/strong><\/p>\n

Title: <\/span>Combinatorial Optimization for Postal Services<\/p>\n

Abstract: <\/span>This project, a collaboration between HEC Li\u00e8ge and bpost, aims to optimize postal delivery operations through advanced mathematical modeling and algorithmic development. Its goal is to sustain bpost delivery operations for letters and parcels by creatingmethods to partition the Belgian territory into several sets of districts, each set corresponding to a specific mailman route. We seek to design robust district sets such that the workload is maintained as balanced as possible among districts, considering stochastic service times and the presence of stochastic customers. Different stochastic versions of the node, edge, and arc routing problem are studied, and the trade-offs associated with achieving robust workload balance are analyzed.<\/p>\n

Funding partner(s): bpost<\/em>
\nProject leader(s): Yasemin Arda, V\u00e9ronique Fran\u00e7ois<\/em>
\nResearcher(s): Yasemin Arda, V\u00e9ronique Fran\u00e7ois, Melek Musa (postdoctoral grant, 01\/2023 \u2013 07\/2023), Oscar Tellez (postdoctoral grant, 04\/2020 – 10\/2022)<\/em><\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>Theoretical\/Methodological contribution<\/span><\/a><\/h4><\/div>
\n

ML4TDQNA (2026-2028)<\/strong><\/em><\/p>\n

Title: Machine Learning Based Analysis of Time-dependent Queueing Networks<\/p>\n

Abstract: Networks of queues are an important tool for modeling and optimization of complex systems such as production systems, hospitals and transportation networks. An important aspect of queueing networks that is often ignored when developing analysis methods is the dependency of their parameters on time. To incorporate this time-dependency in the analysis of queueing networks, each queue in the network needs to be analyzed considering the time-dependency. This project aims at leveraging the power of machine learning methods to build a method for analyzing the outgoing flow from time-dependent queues, and utilize this method as a building block to build a machine learning based queueing network analysis method that can handle time-dependency.<\/p>\n

Funding: Funding programme (Institution) for example, Actions de Recherche Concert\u00e9es (ULi\u00e8ge)
\nCDR funding from FNRS
\nPartner(s): Institutions, enterprises, research centers
\nProject leader(s): Khayyati, Siamak
\nResearcher(s): Khayyati, Siamak<\/em><\/p>\n

WOOD VAL (2023-2027)<\/em><\/strong><\/p>\n

Title: <\/span>M<\/span>athematical optimization methods for <\/span>a <\/span>dual bin<\/span> packing problem <\/span>applied to<\/span>wood reuse<\/span><\/p>\n

Abstract : The increasing demand for raw materials such as wood contributes to the depletion of natural resources and global warming. To curb this phenomenon, a more sustainable and circular use of wood could be developed through the intelligent management of wood waste. Recycling wood waste has several environmental and economic benefits. Among these, wood is an important CO2<\/span> sink and not burning it allows this carbon to be stored for longer. This work focuses on a way of reducing wood waste, which aims to reuse wood rather than recycle it, i.e., not to reduce the value and properties of the material as would be the case if the wood were recycled into pellets, for example. The objective here is to produce CLT panels by assembling, gluing, and cutting wooden slats, which is a variant of the dual bin packing problem.<\/p>\n

Funding: Grant from Sector Council for research and valorisation in Human Sciences, ULi\u00e8ge<\/em>
\nPartner(s): Tom DE MIL (Agro Bio tech, ULi\u00e8ge), Morgane DUMONT (HEC Li\u00e8ge), Bernard FORTZ (HEC Li\u00e8ge)<\/em>
\nProject leader(s): C\u00e9lia PAQUAY<\/em>
\nResearcher(s): Pauline BESSEMANS<\/em><\/p>\n

Robust<\/span> Home Healthcare Planning<\/span> (<\/span>2024<\/span> \u2013 <\/span>2028<\/span>)<\/span><\/em><\/strong><\/p>\n

Title<\/span>: <\/span>Proactive and reactive optimization methods for dynamic and stochastic home healthcare routing and scheduling problems<\/p>\n

Abstract<\/span>: <\/span>Home healthcare routing and scheduling problems (HHCRSPs) are complex combinatorial optimization problems where the medical tasks of geographically dispersed patients must be assigned to available care workers and scheduled considering treatment requirements and patient preferences. The rosters of the care workers must also be determined for the planning horizon while respecting workforce-related constraints. Moreover, those operational processes are subject to unexpected disruptions that can have dramatic effects on the quality of healthcare services. This research project aims at designing novel proactive and reactive optimization methods for the HHCRSPs arising in uncertain and dynamic environments. The goal here is to account for the inherent uncertainty and to generate routes, schedules, and rosters that are robust and responsive when facing disruptions.<\/p>\n

Funding: Research Project (Projet de Recherche – PDR) (F.R.S-FNRS)<\/em>
\nProject leader(s): Yasemin Arda<\/em>
\nResearcher(s): Yasemin Arda, Louise Tassin (doctoral grant, since 10\/2024)<\/em>
\nCollaborator(s): V\u00e9ronique Fran\u00e7ois (QuantOM), Michel Gendreau (CIRRELT Montr\u00e9al),Elise Vandomme (QuantOM)<\/em><\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>PhDs in progress<\/span><\/a><\/h4><\/div>
\n

BESSEMANS, Pauline (2023 – \u2026)<\/strong><\/em><\/p>\n

Title: Mathematical optimization methods for a dual bin packing problem applied to wood reuse<\/p>\n

Abstract: The increasing demand for raw materials such as wood contributes to the depletion of natural resources and global warming. To curb this phenomenon, a more sustainable and circular use of wood could be developed through the intelligent management of wood waste. Recycling wood waste has several environmental and economic benefits. Among these, wood is an important CO2<\/sub> sink and not burning it allows this carbon to be stored for longer. This work focuses on a way of reducing wood waste, which aims to reuse wood rather than recycle it, i.e., not to reduce the value and properties of the material as would be the case if the wood were recycled into pellets, for example. The objective here is to produce CLT panels by assembling, gluing, and cutting wooden slats, which is a variant of the dual bin packing problem.<\/p>\n

Supervisor: PAQUAY, C\u00e9lia<\/em><\/p>\n

DOSSE, Benjamin (2024 \u2013 \u2026 )<\/em><\/strong><\/p>\n

Title: New market designs for renewable electricity trading through mathematical optimization<\/p>\n

Abstract: The increasing penetration of intermittent renewable energy sources has had a significant impact on the Europe market mechanism for electricity trading. The European market has been designed for controllable energy source, in which the production capacity is known in advance. The production capacity of intermittent energy source is known only on delivery time, after the trading takes places, inducing billions of euros of loss in the balancing market. This also brings new challenges on the European transmission network that cannot support the production load when renewable sources production at 100%. We are studying new local market designs adapted to intermittent energy sources and taking into consideration transmission constraints.<\/p>\n

Supervisor(s): J\u00e9r\u00f4me De Boeck, (co-supervisor : Bernard Fortz)<\/em><\/p>\n

LELOUP, Emeline (2020 – \u2026)<\/strong><\/em><\/p>\n

Title: A three-dimensional loading vehicle routing problem with split pickups, promised service times and time windows under real-time disruptions<\/p>\n

Abstract: The first-mile collection problem, which includes collecting and transporting products, has an increasing share in the intricacy of supply chains. Complex challenges must be considered such as time windows, time-dependent travel durations, maximum working duration, cargo stability and reachability. Moreover, parcels collection tends to be more uncertain than delivery as additional pickup requests may pop up, or the number of boxes to collect can change during the day. The pickup process, in which the vehicle is initially empty, is much more able to react to these types of disruptions on-the-fly. The scientific community has devoted a lot of attention to delivery, while the specifics of the pickup process have been substantially overlooked. We study this challenging optimization problem.<\/p>\n

Supervisor<\/em>(s): PAQUAY, C\u00e9lia; PIRONET, Thierry<\/em><\/p>\n

MAHARANI, Anisha<\/em><\/strong> (2020 – …)<\/strong><\/p>\n

Title: Integrated operational scheduling for hospital-at-home<\/p>\n

Abstract: Hospital-at-home (HaH) programmes provide an alternative to acute hospitalization by delivering care in patients\u2019 homes. This work proposes metaheuristic solution methods for a weekly HaH decision-making process in which patient admission, nurse routing, and rerostering decisions must be made simultaneously. To maintain the continuity of ongoing treatments and compliance with working hour regulations, this work incorporates information from consecutive weeks on nurse rosters and already admitted patients. In a first study, we consider admission decisions for the eligible patients of a given week, while in a second study, we also account for stochastic information available for the eligible patients of the coming week.<\/p>\n

Supervisors: ARDA, Yasemin; FRAN\u00c7OIS, V\u00e9ronique<\/em><\/p>\n

Nelie Laura MAKENNE (2023 – …)<\/strong><\/em><\/p>\n

Title: Towards Green AI: Compressing Large Language Models for Sustainable Deployment<\/p>\n

Abstract: Recent advancements in large language models have achieved state-of-the-art performance across a range of natural language processing tasks. However, their substantial computational, memory, and energy requirements limit their deployment in resource-constrained environments. This thesis proposes a compression framework based on singular value decomposition (SVD) to identify informative model parameters, facilitating effective low-rank approximations that reduce redundancy while preserving performance. A layer-wise compression strategy is introduced to regulate the compression process and adaptively adjust model components according to their sensitivity to dimensionality reduction. The environmental impact is assessed through a comprehensive carbon footprint analysis.<\/p>\n

Supervisor(s): \u00a0Ashwin ITTOO<\/em><\/p>\n

TONKA, Jenny<\/em><\/strong> (2021 – …)<\/strong><\/p>\n

Title: Air Transport Ground Operations Management: Digital Twin Building Blocks for Real-Time Monitoring and Process Optimization<\/p>\n

Abstract: Transporting billions of passengers and millions of tons of cargo each year, the air transport industry has become a cornerstone of the global economy. However, the sector must address the complex logistical challenges posed by surging global demand and an increasingly challenging environment. This thesis specifically focuses on ground process operational efficiency, aiming to develop real-time monitoring and optimization strategies for both outbound baggage ground handling and air cargo ground operations. Leveraging the innovative technological framework of digital twins, as well as operations research and machine learning techniques, the thesis develops novel mathematical models, original heuristics, and tailored parametrization protocols for existing solution methods.<\/p>\n

Supervisor: SCHYNS, Micha\u00ebl<\/em><\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>Defended PhDs<\/span><\/a><\/h4><\/div>
\n

BEBRONNE, Elodie (2020 \u2013 2026)<\/strong><\/p>\n

Title: Managerial insights into the nocturnal environment: An interdisciplinary analysis<\/p>\n

Abstract : The cycle of day and night is one of nature’s most enduring rhythms. However, advances in human activity and technology have gradually extended the boundaries of human presence into the night, disrupting this natural cycle. The doctoral thesis explores the sustainable management of the nocturnal environment in response to these changes. We present a novel approach by applying management science principles to a region heavily affected by light pollution. Such a perspective allows questioning the local managerial context, relationships among supply chain actors, acceptability of reducing public lighting, and potential insights from the emerging concept of Industry 5.0. The research is based on archival data, empirical data from 51 interviews with experts over a longitudinal period and 3114 survey responses in a repeated cross-sectional study conducted during the energy crisis.<\/p>\n

Supervisor: LIMBOURG, Sabine<\/em><\/p>\n<\/div><\/div><\/div><\/div><\/div>

<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-109","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/pages\/109","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/comments?post=109"}],"version-history":[{"count":31,"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/pages\/109\/revisions"}],"predecessor-version":[{"id":385,"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/pages\/109\/revisions\/385"}],"wp:attachment":[{"href":"https:\/\/www.quantom.hec.uliege.be\/index.php\/wp-json\/wp\/v2\/media?parent=109"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}