Abstract
In this paper, we analyze the landscape of knapsack problems and propose a new search method called structure oriented search algorithm (SOSA). The heuristic search methods such as a simulated annealing and a genetic algorithm can be applied to complex optimization problems such as combinatorial ones. However, these methods are often redundant and inefficient. The key idea of the SOSA is approximating the landscape structure of the search space, so that the sampling domain can be directly moved to the promising region. The numerical experiments to solve knapsack problems have been conducted and the results are compared with that of genetic algorithms. The experimental results show the effectiveness of our method from the viewpoint of accuracy and calculation cost.
| Original language | English |
|---|---|
| Title of host publication | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
| Pages | 5941-5946 |
| Number of pages | 6 |
| Volume | 6 |
| DOIs | |
| Publication status | Published - 2004 |
| Event | 2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague Duration: 2004 Oct 10 → 2004 Oct 13 |
Other
| Other | 2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 |
|---|---|
| City | The Hague |
| Period | 04/10/10 → 04/10/13 |
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Keywords
- Big-valley structure
- Knapsack problem
- Stochastic optimization
- Structure oriented search algorithm
ASJC Scopus subject areas
- Engineering(all)
Cite this
Structure oriented search algorithm to solve knapsack problems. / Yoshizawa, Hiroki; Hashimoto, Shuji.
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. Vol. 6 2004. p. 5941-5946.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Structure oriented search algorithm to solve knapsack problems
AU - Yoshizawa, Hiroki
AU - Hashimoto, Shuji
PY - 2004
Y1 - 2004
N2 - In this paper, we analyze the landscape of knapsack problems and propose a new search method called structure oriented search algorithm (SOSA). The heuristic search methods such as a simulated annealing and a genetic algorithm can be applied to complex optimization problems such as combinatorial ones. However, these methods are often redundant and inefficient. The key idea of the SOSA is approximating the landscape structure of the search space, so that the sampling domain can be directly moved to the promising region. The numerical experiments to solve knapsack problems have been conducted and the results are compared with that of genetic algorithms. The experimental results show the effectiveness of our method from the viewpoint of accuracy and calculation cost.
AB - In this paper, we analyze the landscape of knapsack problems and propose a new search method called structure oriented search algorithm (SOSA). The heuristic search methods such as a simulated annealing and a genetic algorithm can be applied to complex optimization problems such as combinatorial ones. However, these methods are often redundant and inefficient. The key idea of the SOSA is approximating the landscape structure of the search space, so that the sampling domain can be directly moved to the promising region. The numerical experiments to solve knapsack problems have been conducted and the results are compared with that of genetic algorithms. The experimental results show the effectiveness of our method from the viewpoint of accuracy and calculation cost.
KW - Big-valley structure
KW - Knapsack problem
KW - Stochastic optimization
KW - Structure oriented search algorithm
UR - http://www.scopus.com/inward/record.url?scp=15744387104&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=15744387104&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2004.1401145
DO - 10.1109/ICSMC.2004.1401145
M3 - Conference contribution
SN - 0780385667
VL - 6
SP - 5941
EP - 5946
BT - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ER -