An OR Practitioner's Solution Approach for the Set Covering Problem. - Yun Lu 003; Francis J. Vasko (Int. J. Appl. Metaheuristic Comput., 2015)

Teacher training enhances the teaching-learning-based optimisation metaheuristic when used to solve multiple-choice multidimensional knapsack problems. - Kenneth Zyma; Yun Lu 003; Francis J. Vasko (Int. J. Metaheuristics, 2015)

An empirical study of population-based metaheuristics for the multiple-choice multidimensional knapsack problem. - Francis J. Vasko; Yun Lu 003; Kenneth Zyma (Int. J. Metaheuristics, 2016)

What is the best greedy-like heuristic for the weighted set covering problem? - Francis J. Vasko; Yun Lu 003; Kenneth Zyma (Oper. Res. Lett., 2016)

Simple population-based metaheuristics for the multiple demand multiple-choice multidimensional knapsack problem. - Dylan Gaspar; Yun Lu 003; Myung Soon Song; Francis J. Vasko (Int. J. Metaheuristics, 2020)

Application of Metaheuristic Approaches for the Variable Selection Problem. - Myung Soon Song; Francis J. Vasko; Yun Lu 003; Kyle Callaghan (Int. J. Appl. Metaheuristic Comput., 2022)

An Application of Machine Learning Tools to Predict the Number of Solutions for a Minimum Cardinality Set Covering Problem. - Brooks Emerick; Myung Soon Song; Yun Lu 003; Francis J. Vasko (OLA, 2023)

Statistical analyses of solution methods for the multiple-choice knapsack problem with setups: Implications for OR practitioners. - Myung Soon Song; Yun Lu 003; Dominic Rando; Francis J. Vasko (Expert Syst. Appl., 2025)