Structure oriented search algorithm to solve knapsack problems

Hiroki Yoshizawa; Shuji Hashimoto

doi:10.1109/ICSMC.2004.1401145

Structure oriented search algorithm to solve knapsack problems

Hiroki Yoshizawa, Shuji Hashimoto

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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	https://doi.org/10.1109/ICSMC.2004.1401145
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

Keywords

Big-valley structure
Knapsack problem
Stochastic optimization
Structure oriented search algorithm

ASJC Scopus subject areas

Engineering(all)

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title = "Structure oriented search algorithm to solve knapsack problems",

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.",

keywords = "Big-valley structure, Knapsack problem, Stochastic optimization, Structure oriented search algorithm",

author = "Hiroki Yoshizawa and Shuji Hashimoto",

year = "2004",

doi = "10.1109/ICSMC.2004.1401145",

language = "English",

isbn = "0780385667",

volume = "6",

pages = "5941--5946",

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note = "2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 ; Conference date: 10-10-2004 Through 13-10-2004",

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T1 - Structure oriented search algorithm to solve knapsack problems

AU - Yoshizawa, Hiroki

AU - Hashimoto, Shuji

PY - 2004

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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.

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