Publications
• Song, M., Lin, Pei., Shively-Ertas, E., Lu, Y., and Vasko, F. 2024. “A Practical Approach for Dealing with Hard Knapsack Problems using General-Purpose Integer Programming Software”, International Transactions in Operational Research. http://doi.org/10.1111/itor.13449
• Vasko, F., Lu, Y., Shively-Ertas, E., and Song, M. 2024. “Efficiently Generating Bounded Solutions for Very Large Multiple Knapsack Assignment Problems”, Journal of Computational and Cognitive Engineering, 3(1), 1-7. https://doi.org/10.47852/bonviewJCCE3202921
• Dellinger, A., Lu, Y., Song, M., and Vasko, F. 2023. “Simple Strategies that generate Bounded Solutions for the Multiple-choice Multidimensional Knapsack Problem: a guide for OR Practitioners”, International Transactions in Operational Research, 30(6), 4061-4077. https://doi.org/10.1111/itor.13144
• Emerick, B., Song, M., Lu, Y., Vasko, F. 2023. “An Application of Machine Learning Tools to Predict the Number of Solutions for a Minimum Cardinality Set Covering”, Optimization and Learning, Springer, Cham, 1824, 175-185. https://doi.org/10.1007/978-3-031-34020-8_13
• Vasko, F., Lu, Y., and Song, M. June 2023. “Solving Hard Combinatorial Optimization Problems with General Purpose Integer Programming Software: A Guide for OR Practitioners”, Inside OR. 13
• Shively-Ertas, E., Lu, Y., Song, M., Vasko, F. 2023. "Using General-Purpose Integer Programming Software to Generate Bounded Solutions for the Multiple Knapsack Problem: a Guide for OR Practitioners ", International Journal of Industrial Optimization, 4(1), 16-24. https://doi.org/10.12928/ijio.v4i1.6446
• Song, M., Emerick, B., Lu, Y., and Vasko, F. 2022. “When to use Integer Programming Software to solve large Multi-demand Multidimensional Knapsack Problems: A Guide for Operations Research Practitioners”, Engineering Optimization, 54(5), 894-906. https://doi.org/10.1080/0305215X.2021.1933965
• Song, M., Vasko, F., Lu, Y., and Callaghan, K. 2022. “Application of Metaheuristic Approaches for the Variable Selection Problem”, International Journal of Applied Metaheuristic Computing, 13(1), 1-22. https://doi.org/10.4018/IJAMC.298309
• Dellinger, A., Lu, Y., Song, M., and Vasko, F. 2022. “Generating Bounded Solutions for large and difficult-to-solve Multi-demand Multidimensional Knapsack Problems: A Guide for Operations Research Practitioners”, International Journal of Industrial Optimization, 3(1), 1-17. https://doi.org/10.12928/ijio.v3i1.5073
• McNally, B., Lu, Y., Shively-Ertas, E., Song, M., and Vasko, F. 2021. “A Simple and Effective Methodology for Generating Bounded Solutions for the Set K-Covering and Set Variable K-Covering Problems: a guide for OR practitioners”, Review of Computer Engineering Research, 8(2), 76-95. https://doi.org/10.18488/journal.76.2021.82.76.95
• Dellinger, A., Lu, Y., McNally, B., Song, M., and Vasko, F. 2021. “A simple and efficient technique to generate bounded solutions for the Generalized Assignment Problem: a guide for OR Practitioners” Research Reports on Computer Science, 1(1), 13-34. https://doi.org/10.37256/rrcs.1120221039
• Gaspar, D., Lu, Y., Song, M., and Vasko, F. 2020. “Simple Population-Based Metaheuristics for the Multiple Demand Multiple-Choice Multidimensional Knapsack Problem”, International Journal of Metaheuristics, 7(4), 330-351. https://doi.org/10.1504/IJMHEUR.2020.111600
• Song, M., Vasko, F., Lu, Y., and Callaghan, K. 2020. “Variable Selection with Metaheuristic Methods”, JSM Proceedings. Recent Advances In Statistical Learning And Missing Data Handling. Alexandria, VA: American Statistical Association. 1170-1177.
• Song, M. 2017. “Synthesizing Correlations with Computational Likelihood Approach: Vitamin C Data”, arXiv:1701.08145 [stat.AP].
• Song, M. 2016. “Combining Information by Using Likelihood with Application”, JSM Proceedings. Topics in Statistical Methods and Applications. Alexandria, VA: American Statistical Association. 410-423.
• Hamdan, S., Melhem, N., Porta, P., Song, M., Brent, D. 2013. “Alcohol and Substance Abuse in Parentally Bereaved Youth”, The Journal of Clinical Psychiatry, 74(8), 828-833. https://doi.org/10.4088/JCP.13m08391
• Song, M., and Gleser, L. 2012. “A Numerical Likelihood-based Approach to Combining Correlation Matrices”, Communications in Statistics - Simulation and Computation, 41(9), 1679-1692. https://doi.org/10.1080/03610918.2011.615435
• Song, M., and Gleser, L. 2010. “Numerical Approximation of the Likelihood of Correlation Matrices”, JSM Proceedings. Social Statistics Section. Alexandria, VA: American Statistical Association. 5192-5204.
