How to cite this paper
Kern, Z., Lu, Y & Vasko, F. (2020). An OR practitioner’s solution approach to the multidimensional knapsack problem.International Journal of Industrial Engineering Computations , 11(1), 73-82.
Refrences
Akçay, Y., Li, H., & Xu, S. H. (2007). Greedy algorithm for the general multidimensional knapsack problem. Annals of Operations Research, 150(1), 17.
Baroni, M. D. V., & Varejão, F. M. (2015, November). A shuffled complex evolution algorithm for the multidimensional knapsack problem. In Iberoamerican Congress on Pattern Recognition (pp. 768-775). Springer, Cham.
Boyer, V., Elkihel, M., & El Baz, D. (2009). Heuristics for the 0–1 multidimensional knapsack problem. European Journal of Operational Research, 199(3), 658-664.
Chu, P. C., & Beasley, J. E. (1998). A genetic algorithm for the multidimensional knapsack problem. Journal of Heuristics, 4(1), 63-86.
Fréville, A. (2004). The multidimensional 0–1 knapsack problem: An overview. European Journal of Operational Research, 155(1), 1-21.
Frieze, A. M., & Clarke, M. R. B. (1984). Approximation algorithms for the m-dimensional 0-1 knapsack problem: worst-case and probabilistic analyses. European Journal of Operational Research, 15(1), 100-109.
Baghel, M., Agrawal, S., & Silakari, S. (2012). Survey of metaheuristic algorithms for combinatorial optimization. International Journal of Computer Applications, 58(19), 2709-2716.
Kellerer, H., Pferschy, U., & Pisinger, D. (2004). Multidimensional Knapsack Problems. In Knapsack problems(pp. 235-283). Springer, Berlin, Heidelberg.
Kong, X., Gao, L., Ouyang, H., & Li, S. (2015). Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm. Computers & Operations Research, 63, 7-22.
Laabadi, S., Naimi, M., El Amri, H., & Achchab, B. (2018). The 0/1 Multidimensional Knapsack Problem and Its Variants: A Survey of Practical Models and Heuristic Approaches. American Journal of Operations Research, 8(05), 395.
Labed, S., Gherboudj, A.,& Chikhi, S. (2011) A Modified Hybrid Particle Swarm Optimization Algorithm for Multidimensional Knapsack Problem, International Journal of Computer Applications, 34(2), 11-16.
Lanza-Gutierrez, J. M., Crawford, B., Soto, R., Berrios, N., Gomez-Pulido, J. A., & Paredes, F. (2017). Analyzing the effects of binarization techniques when solving the set covering problem through swarm optimization. Expert Systems with Applications, 70, 67-82.
Meng, T., & Pan, Q. K. (2017). An improved fruit fly optimization algorithm for solving the multidimensional knapsack problem. Applied Soft Computing, 50, 79-93.
Moraga, R. J., DePuy, G. W., & Whitehouse, G. E. (2005). Meta-RaPS approach for the 0-1 multidimensional knapsack problem. Computers & Industrial Engineering, 48(1), 83-96.
Newhart, D. D., Stott, K. L., & Vasko, F. J. (1993). Consolidating product sizes to minimize inventory levels for a multi-stage production and distribution system. Journal of the operational Research Society, 44(7), 637-644.
Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2011). Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Computer-Aided Design, 43(3), 303-315.
Rezoug, A., & Boughaci, D. (2016). A self-adaptive harmony search combined with a stochastic local search for the 0-1 multidimensional knapsack problem. International Journal of Bio-Inspired Computation, 8(4), 234-239.
Rezoug A, Bader-El-Den M., & Boughaci D. (2018) Guided genetic algorithm for the multidimensional knapsack problem, Memetic Computing, 10, 29-42.
Vasko, F. J., Wolf, F. E., & Stott, K. L. (1989). A practical solution to a fuzzy two-dimensional cutting stock problem. Fuzzy Sets and Systems, 29(3), 259-275.
Vasko, F. J., Wolf, F. E., & Pflugrad, J. A. (1991). An efficient heuristic for planning mother plate requirements at Bethlehem Steel. Interfaces, 21(2), 1-7.
Vasko, F. J., Wolf, F. E., Stott, K. L., & Woodyatt, L. R. (1993). Adapting branch-and-bound for real-world scheduling problems. Journal of the Operational Research Society, 44(5), 483-490.
Vasko, F. J., Newhart, D. D., & Strauss, A. D. (2005). Coal blending models for optimum cokemaking and blast furnace operation. Journal of the Operational Research Society, 56(3), 235-243.
Vasko, F. J., & Stott, K. L. (2008). Strategic Planning: OR to the Rescue. OR Insight, 21(3), 26-32.
Vasko, F.J., Lu, Y., & Zyma, K. (2016). An empirical study of population-based metaheuristics for the multiple-choice multidimensional knapsack problem, International Journal of Metaheuristics, 5(3-4), 193-225.
Vasko, F.J., & Y. Lu, Y.(2017). Binarization of continuous metaheuristics to solve the set covering problem: Simpler is better. invited talk, 21st Triennial Conference of The International Federation of Operational Research Societies (IFORS), Quebec, Canada, July 17-21, 2017.
Zyma, K., Lu, Y., & Vasko, F.J. (2015). Teacher training enhances the teaching-learning-based optimization metaheuristic when used to solve multiple-choice multidimensional knapsack problems, International Journal of Metaheuristics, 4(3-4), 268-293.
Baroni, M. D. V., & Varejão, F. M. (2015, November). A shuffled complex evolution algorithm for the multidimensional knapsack problem. In Iberoamerican Congress on Pattern Recognition (pp. 768-775). Springer, Cham.
Boyer, V., Elkihel, M., & El Baz, D. (2009). Heuristics for the 0–1 multidimensional knapsack problem. European Journal of Operational Research, 199(3), 658-664.
Chu, P. C., & Beasley, J. E. (1998). A genetic algorithm for the multidimensional knapsack problem. Journal of Heuristics, 4(1), 63-86.
Fréville, A. (2004). The multidimensional 0–1 knapsack problem: An overview. European Journal of Operational Research, 155(1), 1-21.
Frieze, A. M., & Clarke, M. R. B. (1984). Approximation algorithms for the m-dimensional 0-1 knapsack problem: worst-case and probabilistic analyses. European Journal of Operational Research, 15(1), 100-109.
Baghel, M., Agrawal, S., & Silakari, S. (2012). Survey of metaheuristic algorithms for combinatorial optimization. International Journal of Computer Applications, 58(19), 2709-2716.
Kellerer, H., Pferschy, U., & Pisinger, D. (2004). Multidimensional Knapsack Problems. In Knapsack problems(pp. 235-283). Springer, Berlin, Heidelberg.
Kong, X., Gao, L., Ouyang, H., & Li, S. (2015). Solving large-scale multidimensional knapsack problems with a new binary harmony search algorithm. Computers & Operations Research, 63, 7-22.
Laabadi, S., Naimi, M., El Amri, H., & Achchab, B. (2018). The 0/1 Multidimensional Knapsack Problem and Its Variants: A Survey of Practical Models and Heuristic Approaches. American Journal of Operations Research, 8(05), 395.
Labed, S., Gherboudj, A.,& Chikhi, S. (2011) A Modified Hybrid Particle Swarm Optimization Algorithm for Multidimensional Knapsack Problem, International Journal of Computer Applications, 34(2), 11-16.
Lanza-Gutierrez, J. M., Crawford, B., Soto, R., Berrios, N., Gomez-Pulido, J. A., & Paredes, F. (2017). Analyzing the effects of binarization techniques when solving the set covering problem through swarm optimization. Expert Systems with Applications, 70, 67-82.
Meng, T., & Pan, Q. K. (2017). An improved fruit fly optimization algorithm for solving the multidimensional knapsack problem. Applied Soft Computing, 50, 79-93.
Moraga, R. J., DePuy, G. W., & Whitehouse, G. E. (2005). Meta-RaPS approach for the 0-1 multidimensional knapsack problem. Computers & Industrial Engineering, 48(1), 83-96.
Newhart, D. D., Stott, K. L., & Vasko, F. J. (1993). Consolidating product sizes to minimize inventory levels for a multi-stage production and distribution system. Journal of the operational Research Society, 44(7), 637-644.
Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2011). Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Computer-Aided Design, 43(3), 303-315.
Rezoug, A., & Boughaci, D. (2016). A self-adaptive harmony search combined with a stochastic local search for the 0-1 multidimensional knapsack problem. International Journal of Bio-Inspired Computation, 8(4), 234-239.
Rezoug A, Bader-El-Den M., & Boughaci D. (2018) Guided genetic algorithm for the multidimensional knapsack problem, Memetic Computing, 10, 29-42.
Vasko, F. J., Wolf, F. E., & Stott, K. L. (1989). A practical solution to a fuzzy two-dimensional cutting stock problem. Fuzzy Sets and Systems, 29(3), 259-275.
Vasko, F. J., Wolf, F. E., & Pflugrad, J. A. (1991). An efficient heuristic for planning mother plate requirements at Bethlehem Steel. Interfaces, 21(2), 1-7.
Vasko, F. J., Wolf, F. E., Stott, K. L., & Woodyatt, L. R. (1993). Adapting branch-and-bound for real-world scheduling problems. Journal of the Operational Research Society, 44(5), 483-490.
Vasko, F. J., Newhart, D. D., & Strauss, A. D. (2005). Coal blending models for optimum cokemaking and blast furnace operation. Journal of the Operational Research Society, 56(3), 235-243.
Vasko, F. J., & Stott, K. L. (2008). Strategic Planning: OR to the Rescue. OR Insight, 21(3), 26-32.
Vasko, F.J., Lu, Y., & Zyma, K. (2016). An empirical study of population-based metaheuristics for the multiple-choice multidimensional knapsack problem, International Journal of Metaheuristics, 5(3-4), 193-225.
Vasko, F.J., & Y. Lu, Y.(2017). Binarization of continuous metaheuristics to solve the set covering problem: Simpler is better. invited talk, 21st Triennial Conference of The International Federation of Operational Research Societies (IFORS), Quebec, Canada, July 17-21, 2017.
Zyma, K., Lu, Y., & Vasko, F.J. (2015). Teacher training enhances the teaching-learning-based optimization metaheuristic when used to solve multiple-choice multidimensional knapsack problems, International Journal of Metaheuristics, 4(3-4), 268-293.