A simplified binary harmony search algorithm for large scale 0–1 knapsack problems

Kong, Xiangyong; Gao, Liqun; Ouyang, Haibin; Li, Steven

doi:10.1016/j.eswa.2015.02.015

Cited by 86 publications

(34 citation statements)

References 49 publications

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“…From these tables, we can see that the proposed IBBA-RSS outperforms the other algorithms for all KP instances (KP 21 -KP 32 ). Also, the proposed algorithm saves the commotional time, where it is consumed a small number of iterations compared with the other algorithms [37].…”

Section: Large-scale 0-1 Knapsack Problemsmentioning

confidence: 99%

“…are calculated. On the other hand, the performance of the proposed IBBA-RSS algorithm is compared with six different algorithms that are reported in [37]: NGHS1 [36], SBHS [37], BHS [38], DBHS [39], ABHS [40] and ABHS1 [41]. Table 2 shows the comparisons between the proposed algorithm and six algorithms, where best results are highlighted in bold.…”

Section: Low-dimensional 0-1 Knapsack Problemsmentioning

confidence: 99%

“…In this section, the performance of proposed algorithm is investigated to solve ten low-dimensional 0-1 knapsack problems, where these instances are taken from [36,37]. The required information about test instances such as dimension and parameters is listed in Table 1.…”

Section: Low-dimensional 0-1 Knapsack Problemsmentioning

confidence: 99%

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New binary bat algorithm for solving 0–1 knapsack problem

Rizk‐Allah

Hassanien

2017

Complex Intell. Syst.

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This paper presents a novel binary bat algorithm (NBBA) to solve 0-1 knapsack problems. The proposed algorithm combines two important phases: binary bat algorithm (BBA) and local search scheme (LSS). The bat algorithm enables the bats to enhance the exploration capability while LSS aims to boost the exploitation tendencies and, therefore, it can prevent the BBA-LSS from the entrapment in the local optima. Moreover, the LSS starts its search from BBA found so far. By this methodology, the BBA-LSS enhances the diversity of bats and improves the convergence performance. The proposed algorithm is tested on different size instances from the literature. Computational experiments show that the BBA-LSS can be promise alternative for solving large-scale 0-1 knapsack problems.

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Section: Large-scale 0-1 Knapsack Problemsmentioning

confidence: 99%

Section: Low-dimensional 0-1 Knapsack Problemsmentioning

confidence: 99%

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New binary bat algorithm for solving 0–1 knapsack problem

Rizk‐Allah

Hassanien

2017

Complex Intell. Syst.

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“…The research on knapsack problem based on CS is not enough. Additionally, although many efficient methods have emerged for the 0-1KP problems [62][63] , in fact, further work is needed to resolve some new and harder 0-1 knapsack problems hidden in the real world, or rather, the correlation between the weight and the profit of the items may not be more concerned. In [62][63] , although 10 low-dimensional and 16 randomly-generated high-dimensional 0-1KP instances are used, the latter did not consider the correlation between the profits and weights of the items.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0–1 Knapsack Problems

Feng¹,

Wang²,

Gao³

2016

IJCIS

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Cuckoo search (CS) is a novel biologically inspired algorithm and has been widely applied to many fields. Although some binary-coded CS variants are developed to solve 0-1 knapsack problems, the search accuracy and the convergence speed are still needed to further improve. According to the analysis of the shortcomings of the standard CS and the advantage of the global harmony search (GHS), a novel hybrid meta-heuristic optimization approach, called cuckoo search Algorithm with global harmony search (CSGHS), is proposed in this paper to solve 0-1 knapsack problems (KP) more effectively. In CSGHS, it is the combination of the exploration of GHS and the exploitation of CS that makes the CSGHS efficient and effective. The experiments conducted demonstrate that the CSGHS generally outperformed the binary cuckoo search, the binary shuffled frog-leaping algorithm and the binary differential evolution in accordance with the search accuracy and convergence speed. Therefore, the proposed hybrid algorithm is effective to solve 0-1 knapsack problems.

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“…In [17], Zhang proposed a harmony search algorithm while it adopted the parallel updating strategy rather than serial updating strategy. In [18], Kong proposed a simplified binary harmony search algorithm for large scale KP01. In [19], an algorithm based on amoeboid organism was proposed by transforming the longest path into the shortest path.…”

Section: Introductionmentioning

confidence: 99%

Solving 0-1 knapsack problem by greedy degree and expectation efficiency

Wang

Huang

et al. 2016

Applied Soft Computing

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It is well known that 0-1 knapsack problem (KP01) plays an important role in both computing theory and many real life applications. Due to its NP-hardness, lots of impressive research work has been performed on many variants of the problem. Inspired by region partition of items, an effective hybrid algorithm based on greedy degree and expectation efficiency (GDEE) is presented in this paper. In the proposed algorithm, initially determinate items region, candidate items region and unknown items region are generated to direct the selection of items. A greedy degree model inspired by greedy strategy is devised to select some items as initially determinate region. Dynamic expectation efficiency strategy is designed and used to select some other items as candidate region, and the remaining items are regarded as unknown region. To obtain the final items to which the best profit corresponds, static expectation efficiency strategy is proposed whilst the parallel computing method is adopted to update the objective function value. Extensive numerical investigations based on a large number of instances are conducted. The proposed GDEE algorithm is evaluated against chemical reaction optimization algorithm and modified discrete shuffled frog leaping algorithm. The comparative results show that GDEE is much more effective in solving KP01 than other algorithms and that it is a promising tool for solving combinatorial optimization problems such as resource allocation and production scheduling.

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A simplified binary harmony search algorithm for large scale 0–1 knapsack problems

Cited by 86 publications

References 49 publications

New binary bat algorithm for solving 0–1 knapsack problem

New binary bat algorithm for solving 0–1 knapsack problem

A Novel Hybrid Cuckoo Search Algorithm with Global Harmony Search for 0–1 Knapsack Problems

Solving 0-1 knapsack problem by greedy degree and expectation efficiency

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