Publications

(last update: Jun 2022)


Publications:

    1. Thevenin, S., Adulyasak, Y., Cordeau, J.-F., 2022. Stochastic Dual Dynamic Programming for Multi-Echelon Lot-sizing with Component Substitution. INFORMS Journal on Computing (To appear). [pdf] (working paper version)

    2. Wu, L., Adulyasak, Y., Cordeau, J.-F., Wang, S., 2022. Vessel Service Planning in Seaports. Operations Research (In Press). [Link] [Codes and Instances]

    3. Zhang, G., Zhu, N., Ma, S., Adulyasak, Y., 2022. Robust Drone Selective Routing Problem in Humanitarian Transportation Network Assessment. European Journal of Operational Research. (In press). [Link]

    4. Martinez, K., Adulyasak, Y., Jans, R., 2022. Logic–Based Benders Reformulations for Integrated Process Configuration and Production Planning Problems. INFORMS Journal on Computing (In press). [Link]

    5. 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]

    6. Nguyen, D.-T., Adulyasak, Y., Cordeau, J.-F., Ponce, S., 2021. Data-Driven Operations and Supply Chain Management: Established Research Clusters from 2000 to early 2020. International Journal of Production Research (In Press) [Link][Supplement]

    7. 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]

    8. Cheng, C., Adulyasak, Y., Rousseau, L.-M., 2021. Robust Facility Location under Disruptions. INFORMS Journal on Optimization. 3(3). 298-314. [Link]

    9. 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

    10. 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]

    11. 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]

    12. 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]

    13. 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]

    14. 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]

    15. 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]

    16. 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 [Github] by M. Deudon.

    17. 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]

    18. 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]

    19. Adulyasak, Y., Jaillet, P., 2016. Models and Algorithms for Stochastic and Robust Vehicle Routing with Deadlines. Transportation Science 50 (2). 608-626. [Link] [Supplement]

    20. Adulyasak, Y., Cordeau, J.-F., Jans, R., 2015. Benders Decomposition for Production Routing under Demand Uncertainty. Operations Research 63 (4). 851-867. [Link] [Supplement]

    21. 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]

    22. 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]

    23. 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]

    24. 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]

    25. Varakantham, P., Adulyasak, Y., Jaillet, P., 2014. Decentralized Stochastic Planning with Anonymity in Interactions. 28th Conference on Artificial Intelligence (AAAI). [pdf]

    26. 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]

    27. 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:

    1. Bayani, M., Rostami, B., Adulyasak, Y., Rousseau, L.-M., A Dual Bounding Framework For Binary Quadratic Combinatorial Optimization. [pdf] (Under revision at INFORMS Journal on Computing)

    2. Metzker, P., Thevenin, S., Adulyasak, Y., Dolgui, A., Robust optimization for lot-sizing problems under yield uncertainty. [pdf] (Under revision at Computers & Operations Research)

    3. Khern-am-nuai, W., So, H., Cohen, M., and Adulyasak, Y., Selecting Cover Images for Restaurant Reviews: AI vs. Wisdom of the Crowd. [pdf] (Under revision at Manufacturing & Service Operations Management)

      • Finalist - 2021 INFORMS Service Science Paper Awards

    4. Dodin, P., Xiao, J., Adulyasak, Y., Etebari Alamdari, N., Gauthier, L., Grangier, P., Lemaitre, P., Hamilton, W. L., Bombardier Aftermarket Demand Forecast with Machine Learning. [pdf] (Under revision at INFORMS Journal on Applied Analytics)

    5. Adulyasak, Y., Benomar, O., Chaouachi, A., Cohen, M., Khern-am-nuai, W., Data Analytics to Detect Panic Buying and Improve Products Distribution Amid Pandemic. [pdf] (Submitted)

    6. Cheng, C., Yu, Q., Adulyasak, Y., Rousseau, L.-M., Reliable Facility Location Under Event-Correlated Uncertainty. [pdf] (Submitted)

    7. 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)

    8. Tanlamai, J., Khern-am-nuai, W., and Adulyasak, Y., Identifying Arbitrage Opportunities in Retail Markets with Predictive Analytics. [pdf] (Submitted)

    9. Cheng, C., Adulyasak, Y., Rousseau, L.-M., Sim, M., Robust Drone Delivery with Weather Information. [pdf] (Submitted)

    10. Adulyasak, Y., Krause, M., Cohen, M., Khern-am-nuai, W., Retail Analytics in the New Normal. [pdf] (Submitted)

    11. Mahéo, A., Belieres, S., Adulyasak, Y., Cordeau, J.-F., Unified Branch-and-Benders-Cut for Two-Stage Stochastic Mixed-Integer Programs. [pdf] (Submitted)

    12. Zhang, G., Jia, N., Zhu, N., He, L., Adulyasak, Y., Humanitarian Relief Network Design by Two-stage Distributionally Robust Optimization. (Submitted)

    13. Wu, L., Adulyasak, Y., Cordeau, J.-F., Optimizing Freight Procurement for Transportation-Inventory Systems Under Supply and Demand Uncertainty. [pdf] (Submitted)


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 Access 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:

*Please email me if the links do not work

  • Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem

Instances

  • 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]) (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 - [download]

      • Details of the exact solutions - [download]