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As a solution algorithm for Unbounded Knapsack Problem, the\ud performance analysis of density-ordered greedy heuristic, weight-ordered\ud greedy heuristic, value-ordered greedy heuristic, extended greedy\ud heuristic and total-value heuristic has been done. Empirical experiments\ud on different test problems have been analysed and reported. Problem\ud instances with a very large number of undominated items were generated\ud in addition to the types of instances suggested by Martello and Toth\ud (1990). Theoretically, the lower bound on the performance for total-value\ud heuristic is better than the corresponding lower bounds for the densityordered\ud greedy heuristic and the extended greedy heuristic as discussed\ud by White (1992) and Kohli and Krishnamurti (1992). The computational\ud tests fail to show clear superiority of any particular heuristic algorithm,\ud although each heuristic produces good quality solutions. If the\ud combination of the density-ordered greedy and the total-value greedy\ud heuristics are considered then the combination shows complementary\ud effect. A new heuristic algorithm incorporating the structural properties of\ud the density-ordered greedy heuristic and the total-value greedy heuristic\ud is developed and its complementary effect studied. It was found that the\ud combination of the density-ordered greedy heuristic, the extended greedy\ud heuristic, the total-value greedy heuristic and the new complementary\ud heuristic gives a better performance result than the single best heuristic in\ud the combination

Topics:
0102 Applied Mathematics, 0103 Numerical and Computational Mathematics, School of Engineering and Science, applied mathematics, heuristic programming, NP-complete problems

Year: 1997

OAI identifier:
oai:eprints.vu.edu.au:17924

Provided by:
Victoria University Eprints Repository

Downloaded from
http://vuir.vu.edu.au/17924/1/IYER_1997compressed.pdf

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