Publications

(last update: Jun 2021)


Publications:

    1. Wu, L., Adulyasak, Y., Cordeau, J.-F., Wang, S., 2021. Vessel Service Planning in Seaports. Operations Research (To appear) [pdf: working paper version] [Codes and Instances]

    2. Martinez, K., Adulyasak, Y., Jans, R., 2021. Logic–Based Benders Reformulations for Integrated Process Configuration and Production Planning Problems. INFORMS Journal on Computing (To appear) [pdf: working paper version]

    3. 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 (To appear) [pdf: working paper version][Supplement]

    4. Yu, Q., Adulyasak, Y., Rousseau, L.-M., Zhu, N., Ma, S., 2021. Team Orienteering with Time-Varying Profit. INFORMS Journal on Computing (In press). [Link] [Instances]

    5. 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]

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

    7. 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

    8. 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]

    9. 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]

    10. 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]

    11. 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]

    12. 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]

    13. 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]

    14. 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.

    15. 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]

    16. 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]

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

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

    19. 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]

    20. 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]

    21. 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]

    22. 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]

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

    24. 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]

    25. 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. 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] (Under revision at Production and Operations Management)

    2. Thevenin, S., Adulyasak, Y., Cordeau, J.-F., Stochastic Dual Dynamic Programming for Multi-Echelon Lot-sizing with Component Substitution. [pdf] (Under revision at INFORMS Journal on Computing)

    3. Krause, M.,Adulyasak, Y., Cohen, M., Khern-am-nuai, W., Leveraging Data & AI to Excel in a Post-Pandemic Retail World. (Under revision at Management and Business Review)

    4. Zhang, G., Zhu, N., Ma, S., Adulyasak, Y., Robust Drone Selective Routing Problem in Humanitarian Transportation Network Assessment. [pdf] (Under revision at European Journal of Operational Research)

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

    6. 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)

    7. Khern-am-nuai, W., So, H., Cohen, M., and Adulyasak, Y., Selecting Cover Images for Restaurant Reviews: AI vs. Wisdom of the Crowd. [pdf] (Submitted)

      • Finalist - 2021 INFORMS Service Science Paper Awards

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

    11. Bayani, M., Rostami, B., Adulyasak, Y., Rousseau, L.-M., A Dual Bounding Framework For Binary Quadratic Combinatorial Optimization. [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. Metzker, P., Thevenin, S., Adulyasak, Y., Dolgui, A., Robust optimization for lot-sizing problems under yield uncertainty. [pdf] (Submitted)

    14. 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] (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]