Abstract
The Multiple-Choice Multi-Dimension Knapsack Problem (MMKP) is a variant of the 0-1 Knapsack Problem, an NP-Hard problem. Hence algorithms for finding the exact solution of MMKP are not suitable for application in real time decision-making applications, like quality adaptation and admission control of an interactive multimedia system. This paper presents two new heuristic algorithms, M-HEU and I-HEU for solving MMKP. Experimental results suggest that M-HEU finds 96% optimal solutions on average with much reduced computational complexity and performs favorably relative to other heuristic algorithms for MMKP. The scalability property of I-HEU makes this heuristic a strong candidate for use in real time applications.
Cite
CITATION STYLE
Akbar, M. M., Manning, E. G., Shoja, G. C., & Khan, S. (2001). Heuristic solutions for the multiple-choice multi-dimension knapsack problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2074, pp. 659–668). Springer Verlag. https://doi.org/10.1007/3-540-45718-6_71
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