(last update: Jun 2025)
Publications:
Tu, X., Adulyasak, Y., Akbarzadeh, N., Delage, E., 2025. Fair Resource Allocation in Weakly Coupled Markov Decision Processes. 28th International Conference on Artificial Intelligence and Statistics (AISTATS) [Link].
2025 CORS Student Paper Competition (2nd Place) [Link]
Akbarzadeh, N., Adulyasak, Y., Delage, E., 2025. Planning and Learning in Risk-Aware Restless Multi-Arm Bandit Problem. 28th International Conference on Artificial Intelligence and Statistics (AISTATS) [Link].
Rahal, S., Arslan, O., Dems, A., Adulyasak, Y., Cordeau, J.-F., 2025. Facility Location with Modular Capacity under Demand Uncertainty: An Industrial Case Study. INFOR: Information Systems and Operational Research (Online). [Link] (working paper version [pdf])
Metzker, P., Thevenin, S., Adulyasak, Y., Dolgui, A., 2025. Distributionally Robust Optimization for the Multi-Period Multi-Item Lot-Sizing Problems under Yield Uncertainty. IEEE Transactions on Automation Science and Engineering 22, 11731-11752. [Link] (working paper version [pdf])
Wang, W., Adulyasak, Y., Cordeau, J.-F., He, G., 2025. The Heterogeneous-Fleet Electric Vehicle Routing Problem with Nonlinear Charging Functions. Transportation Research Part C: Emerging Technologies 170, 104932. [Link] (working paper version [pdf])
Cheng, C., Adulyasak, Y., Rousseau, L.-M., 2024. Robust Drone Delivery with Weather Information. Manufacturing & Service Operations Management 26(4), 1189-1585. [Link] (working paper version [pdf])
Wu, F., Adulyasak, Y., Cordeau, J.-F., 2024. Modeling and Solving the Traveling Salesman Problem with Speed Optimization for a Plug-in Hybrid Electric Vehicle. Transportation Science 58(3), 562-577. [Link] (working paper version [pdf])
Bayani, M., Rostami, B., Adulyasak, Y., Rousseau, L.-M., 2024. A Dual Bounding Framework Through Cost Splitting for Binary Quadratic Optimization. INFORMS Journal on Computing 36(6), 1501-1521. [Link] (working paper version [pdf])
Khern-am-nuai, W., So, H., Cohen, M., and Adulyasak, Y., 2024. Selecting Cover Images for Restaurant Reviews: AI vs. Wisdom of the Crowd. Manufacturing & Service Operations Management 26(4), 330-349. [Link] (working paper version [pdf])
Finalist - 2021 INFORMS Service Science Paper Awards
Xia, W., Mishra, J., Adulyasak, Y., 2024. Seaport adaptation and capacity investments under inter-port competition and climate-change uncertainty. Transportation Research Part D: Transport and Environment 130, 104183. [Link] (working paper version [pdf])
Mahéo, A., Belieres, S., Adulyasak, Y., Cordeau, J.-F., 2024. Unified Branch-and-Benders-Cut for Two-Stage Stochastic Mixed-Integer Programs. Computers & Operations Research 164, 106526. [Link] (working paper version [pdf])
Adulyasak, Y., Cohen, M., Khern-am-nuai, W., Krause, M., 2024. Retail Analytics in the New Normal: The Influence of Artificial Intelligence and the Covid-19 Pandemic. IEEE Engineering Management Review vol. 52, no. 1, pp. 268-280. [Link] (working paper version [pdf])
Cheng, C., Yu, Q., Adulyasak, Y., Rousseau, L.-M., 2024. Distributionally Robust Facility Location with Uncertain Facility Capacity and Customer Demand. Omega: The International Journal of Management Science 122, 102959. [Link] (working paper version [pdf])
Sereshti, N., Adulyasak, Y., Jans, R., 2024. Managing Flexibility in Stochastic Multi-Level Lot Sizing Problem with Service Level Constraints. Omega: The International Journal of Management Science 122, 102957. [Link]
Metzker, P., Thevenin, S., Adulyasak, Y., Dolgui, A., 2024. Adaptive Robust Optimization for Lot-Sizing under Yield Uncertainty. European Journal of Operational Research 313(12). 513-526. [Link]
Zhang, G., Jia, N., Zhu, N., He, L., Adulyasak, Y., 2023. Humanitarian Relief Network Design by Two-stage Distributionally Robust Optimization. Transportation Research Part B: Methodological 176, 102805. [Link]
Belieres, S., Adulyasak, Y., Cordeau, J.-F., 2023. Scheduling Multi-staged Jobs on Parallel Identical Machines and a Central Server with Sequence-dependent Setup Times: An Application to an Automated Kitchen. Computers & Operations Research 160, 106387. [Link] [pdf] (working paper version)
Tanlamai, J., Khern-am-nuai, W., and Adulyasak, Y., 2023. Identifying Arbitrage Opportunities in Retail Markets with Predictive Analytics. AI & Soc. [Link] [pdf] (working paper version)
Dodin, P., Xiao, J., Adulyasak, Y., Etebari Alamdari, N., Gauthier, L., Grangier, P., Lemaitre, P., Hamilton, W. L., 2023. Bombardier Aftermarket Demand Forecast with Machine Learning. INFORMS Journal on Applied Analytics 53(6), 389-465. [Link] [pdf] (working paper version)
Zhang, G., Zhu, N., Ma, S., Adulyasak, Y., 2023. Robust Drone Selective Routing Problem in Humanitarian Transportation Network Assessment. European Journal of Operational Research 305, no 1, 400-428. [Link]
Adulyasak, Y., Benomar, O., Chaouachi, A., Cohen, M., Khern-am-nuai, W., 2023. Using AI to Detect Panic Buying and Improve Products Distribution amid Pandemic. AI & Soc. [Link] [pdf] (working paper version)
Metzker, P., Thevenin, S., Adulyasak, Y., Dolgui, A., 2023. Robust Optimization for Lot-Sizing Problems under Yield Uncertainty. Computers & Operations Research 149, 106025. [Link]
Wu, L., Adulyasak, Y., Cordeau, J.-F., Wang, S., 2022. Vessel Service Planning in Seaports. Operations Research 70 (4), 2032-2053. [Link] [Codes and Instances]
Thevenin, S., Adulyasak, Y., Cordeau, J.-F., 2022. Stochastic Dual Dynamic Programming for Multi-Echelon Lot-sizing with Component Substitution. INFORMS Journal on Computing. 34(6), 3151-3169. [Link] [Codes and Instances].
Martinez, K., Adulyasak, Y., Jans, R., 2022. Logic–Based Benders Reformulations for Integrated Process Configuration and Production Planning Problems. INFORMS Journal on Computing 34 (4), 2177-2191. [Link]
Yu, Q., Adulyasak, Y., Rousseau, L.-M., Zhu, N., Ma, S., 2022. Team Orienteering with Time-Varying Profit. INFORMS Journal on Computing. 34(1), 262-280. [Link] [Instances]
Nguyen, D.-T., Adulyasak, Y., Cordeau, J.-F., Ponce, S., 2022. Data-Driven Operations and Supply Chain Management: Established Research Clusters from 2000 to early 2020. International Journal of Production Research 60 (17), 5407-5431. [Link][Supplement]
Thevenin, S., Adulyasak, Y., Cordeau, J.-F., 2021. Material Requirements Planning Under Demand Uncertainty Using Stochastic Optimization. Production and Operations Management 30 (2). 475-493. [Link] [Supplement] [Codes and Instances]
Cheng, C., Adulyasak, Y., Rousseau, L.-M., 2021. Robust Facility Location under Disruptions. INFORMS Journal on Optimization. 3(3). 298-314. [Link]
Sereshti, N., Adulyasak, Y., Jans, R., 2021. The Value of Aggregate Service Levels in Stochastic Lot Sizing Problem. Omega: The International Journal of Management Science 102. 102335. [Link]
Best Paper Awards 2021 - Omega
Hoogeboom, M., Adulyasak, Y., Dullaert, W., Jaillet, P. 2021. The Robust Vehicle Routing Problem with Time Window Assignments. Transportation Science. 55 (2). 275-552. [Link]
Cheng, C., Adulyasak, Y., Rousseau, L.-M., 2021. Robust Facility Location Under Demand Uncertainty and Facility Disruptions. Omega: The International Journal of Management Science 103. 102429. [Link]
Nguyen, D.-T., Adulyasak, Y., Landry, S., 2021. Bullwhip Effect in Rule-Based Supply Chain Planning Systems: A Case-Based Simulation at a Hard Goods Retailer. Omega: The International Journal of Management Science 98. 102121. [Link]
Yarkony, J., Adulyasak, Y., Singh, M., Desaulniers, G. 2020. Data Association via Set Packing for Computer Vision Applications. INFORMS Journal on Optimization 2(3). 145-228. [Link]
Cheng, C., Adulyasak, Y., Rousseau, L.-M., 2020. Drone Routing with Energy Function: Formulation and Exact Algorithm. Transportation Research Part B: Methodological 139. 364-387. [Link]
Martinez, K., Adulyasak, Y., Jans, R., Morabito, R., Toso, E.A.V., 2019. An Exact Optimization Approach for an Integrated Process Configuration, Lot-Sizing and Scheduling Problem. Computers & Operations Research 103. 310-323. [Link]
Deudon, M., Cournut, P., Lacoste, A., Adulyasak, Y., Rousseau, L.-M., 2018. Learning Heuristics for the TSP by Policy Gradient. In: van Hoeve WJ. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR). Lecture Notes in Computer Science, vol 10848. [Link]. Here is the excellent [Git] by M. Deudon.
Ahmed, A., Varakantham, P., Lowalekar, M. , Adulyasak Y., Jaillet, P., 2017. Sampling based Approaches for Minimizing Regret in Uncertain Markov Decision Problems (MDPs). Journal of Artificial Intelligence Research 59. 229-264. [pdf]
Ghosh, S., Varakantham, P., Adulyasak, Y., Jaillet, P., 2017. Dynamic Redeployment to Reduce Lost Demand in Bike Sharing Systems. Journal of Artificial Intelligence Research 58, 387-430. [pdf]
Adulyasak, Y., Jaillet, P., 2016. Models and Algorithms for Stochastic and Robust Vehicle Routing with Deadlines. Transportation Science 50 (2). 608-626. [Link] [Supplement]
Adulyasak, Y., Cordeau, J.-F., Jans, R., 2015. Benders Decomposition for Production Routing under Demand Uncertainty. Operations Research 63 (4). 851-867. [Link] [Supplement]
Ghosh, S., Varakantham, P., Adulyasak, Y., Jaillet, P., 2015. Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems. 25th International Conference on Automated Planning and Scheduling (ICAPS). [pdf]
Adulyasak, Y., Varakantham, P., Jaillet, P., 2015. Solving Uncertain MDPs with Objectives that are Separable over Instantiations of Model Uncertainty. 29th Conference on Artificial Intelligence (AAAI). [pdf]
Adulyasak, Y., Cordeau, J.-F., Jans, R., 2014. The Production Routing Problem: A Review of Formulations and Solution Algorithms. Computers & Operations Research 55. 141-152. [Link]
Adulyasak, Y., Cordeau, J.-F., Jans, R., 2014. Formulations and Branch-and-Cut Algorithms for Multivehicle Production and Inventory Routing Problems. INFORMS Journal on Computing 26 (1). 103-120. [Link] [Supplement] [instances and results]
Adulyasak, Y., Cordeau, J.-F., Jans, R., 2014. Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem. Transportation Science 48 (1). 20-45. [Link] [instances and results]
Varakantham, P., Adulyasak, Y., Jaillet, P., 2014. Decentralized Stochastic Planning with Anonymity in Interactions. 28th Conference on Artificial Intelligence (AAAI). [pdf]
Ahmed, A., Varakantham, P., Adulyasak, Y., Jaillet, P., 2013. Regret based Robust Solutions for Uncertain Markov Decision Processes. Advances in Neural Information Processing Systems (NeurIPS) 26. [pdf]
Submitted articles:
Wu, F., Adulyasak, Y., Cordeau, J.-F., The Routing-and-Driving Problem for Plug-in Hybrid Electric Vehicles. [pdf] (Under revision at INFORMS Journal on Computing)
Wang, E., Adulyasak, Y., Cordeau, J.-F., Gao, Z., Yang, L., Joint Rolling Stock and Crew Scheduling in Urban Rail Networks. [pdf] (Under revision at Transportation Science)
2024 RAS Student Paper Competition (2nd Place) - INFORMS [Link]
Thevenin, S., Adulyasak, Y., Prescott‐Gagnon, E., Moisan, T., Multi-Item Inventory Replenishment Planning for Intermittent Demand Using Stochastic Optimization. [pdf] (R&R at Production and Operations Management)
Tanlamai, J., Khern-am-nuai, W., Kar, W., and Adulyasak, Y., The Implications of Generic Responses in Online Customer Service Operations. [pdf] (R&R at Production and Operations Management)
Nguyen, D.-T., Adulyasak, Y., Cordeau, J.-F., Khern-am-nuai, W., Framework for Affinity-Based Personalized Review Recommendation. [pdf] (Under revision at Service Science)
Avishan, F., Dems, A., Adulyasak, Y., Arslan, O., Cordeau, J.-F., Inventory Routing with Heterogeneous Vehicles and Backhauling. [pdf] (Under revision at Transportation Research Part E: Logistics and Transportation Review)
Hosseini, S.-S., Adulyasak, Y., Rousseau, L.-M., Consistent Home Health Care Routing and Scheduling Problem Under Time Uncertainty. [pdf] (Under revision at Transportation Research Part E: Logistics and Transportation Review)
Zhu, L., Adulyasak, Y., Rousseau, L.-M., Partial-Outsourcing Strategy for the Vehicle Routing Problem with Stochastic Demands. [pdf] (Submitted)
Yoo, C., Khern-am-nuai, W., Tanlamai, J., and Adulyasak, Y., Haters Gonna Hate? How Removing Downvote Option Impacts Discussions on Online Forum. [pdf] (Submitted)
Wu, L., Shan, W., Adulyasak, Y., Cordeau, J.-F., Scalable Multi-Stage Stochastic Optimization for Freight Procurement in Transportation-Inventory Systems. [pdf] (Submitted)
Ghaniabadi, M., Adulyasak, Y., Fleischmann, M., Jans, R., A Newsvendor Problem with Holding Costs in a Multi-Stage Supply Chain. (Submitted)
Bayani, M., Adulyasak, Y., Rousseau, L.-M., Learning and Modeling Implicit Constraints in Optimization Models through Decision Trees. [pdf] (Submitted)
van Twiller, J., Adulyasak, Y., Delage, E., Grbic, D., Jensen, R.-M., Navigating Demand Uncertainty in Container Shipping: Deep Reinforcement Learning for Enabling Adaptive and Feasible Master Stowage Planning. [arXiv] (Submitted)
Jalal Osorio, A., Adulyasak, Y., Jans, R., Morabito, R., Toso, E., An Integrated Location-Inventory-Transportation Problem under Demand Uncertainty. [pdf] (Submitted)
Wang, W., Adulyasak, Y., Cordeau, J.-F., Electric Vehicle Routing with Heterogeneous Charging Stations. (Submitted)
Martinez, K., Adulyasak, Y., Jans, R., Stochastic Optimization for Template Design Problem. (Submitted)
Wu, L., Mendoza, J. E., Adulyasak, Y., Cordeau, J.-F., Fleet and Infrastructure Planning for Heavy-duty Electric Vehicles with Opportunity Charging. (Submitted)
Case study:
Rancourt, M.-È., Dufour, É., Silvestri, S., Adulyasak, Y. The Kampala Alternative: Optimizing the Humanitarian Supply Chain in East Africa, Revue internationale de cas en gestion, vol. 21, no 4, 2023, p. 1-7. [Link]
Best Business Case Award 2024 - HEC Montréal [Link]
Nguyen, D.-T., Adulyasak, Y., Landry, S., Roy, J., Beaulieu, M., 2021. Princess Auto: Changing the Supply Chain Management Landscape with Flowcasting. Revue internationale de cas en gestion 19(4), 1-18. [HBR Link]
Miscellaneous:
Desrosiers, J., Jans, R. Adulyasak, Y., 2013. Improved Column Generation Algorithms for Clustering Problems. GERAD Tech Rep. G-2013-26. [pdf]
PhD thesis:
Adulyasak, Y., 2012. Models and Solution Algorithms for Production Routing Problems. HEC Montréal. [pdf]
Patents:
Yarkony, J., Adulyasak, Y., Singh, M. K., Desaulniers, G., Computer Vision Systems and Methods for Machine Learning Using a Set Packing Framework. US Patent App. 16/870,492.
Adulyasak, Y., Cordeau, J-F., Prescott-Gagnon, E., Raymond, V., Thevenin, S. System and Method of Calculating Order Policy for Production Planning with Stochastic Demand. US Patent App.
Moison, T., Prescott-Gagnon, E., Adulyasak, Y., Use of Markov Chain to Assess the Quality of a (s, S) Inventory Policy. US Patent App.
Adulyasak, Y., Moison, T., Prescott-Gagnon, E. A Distribution-Independent Inventory Optimization Approach under Multiple Service Level Targets. US Patent 10,977,609.
Adulyasak, Y., Vallée, J., Hudon, C., Lewis, G. An Attribute-Based Data Analytics Framework for Transferable Demand Analysis. US Patent App.
Instances and Results:
Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem
Instances
Instance set A (Archetti et al. instances) - [download link]
Instance set B (Boudia et al. instances) - [download link]
Formulations and Branch-and-Cut Algorithms for Multi-Vehicle Production and Inventory Routing Problems
Instances
MVPRP instances - generated from the instance set A above (can be obtained here [download])
MVIRP instances - generated from the instances from www-c.eco.unibs.it/~bertazzi/abls.zip (can also be downloaded here - [download link]) (note: see computational experiments section of the paper for the details of the instance generation)
Detailed results
Details of the best heuristic solutions generated by Op-ALNS - See ALNS-results.xls from the download link below
Details of the exact solutions - See BC-results.xls from the download link below