Approximating Solutions to the Knapsack Problem Using the Lagrangian Dual Framework

Author:

Keegan MitchellORCID,Abolghasemi MahdiORCID

Publisher

Springer Nature Singapore

Reference19 articles.

1. Palgrave Advances in the Economics of Innovation and Technology;M Abolghasemi,2023

2. Abolghasemi, M., Abbasi, B., Babaei, T., HosseiniFard, Z.: How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function. arXiv preprint arXiv:2105.06618 (2021)

3. Abolghasemi, M., Abbasi, B., HosseiniFard, Z.: Machine learning for satisficing operational decision making: a case study in blood supply chain. Int. J. Forecast. (2023)

4. Abolghasemi, M., Esmaeilbeigi, R.: State-of-the-art predictive and prescriptive analytics for IEEE CIS 3rd technical challenge. arXiv preprint arXiv:2112.03595 (2021)

5. Bengio, Y., Lodi, A., Prouvost, A.: Machine learning for combinatorial optimization: a methodological tour d’Horizon. Eur. J. Oper. Res. 290(2), 405–421 (2021)

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