An improved adaptive binary Harmony Search algorithm

Wang, Ling; Yang, Ruixin; Xu, Yin; Niu, Qun; Pardalos, Pãnos M.; Fei, Minrui

doi:10.1016/j.ins.2012.12.043

Cited by 115 publications

(61 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

New binary bat algorithm for solving 0–1 knapsack problem

Rizk‐Allah

Hassanien

2017

Complex Intell. Syst.

View full text Add to dashboard Cite

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.

show abstract

Section: Low-dimensional 0-1 Knapsack Problemsmentioning

confidence: 99%

New binary bat algorithm for solving 0–1 knapsack problem

Rizk‐Allah

Hassanien

2017

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…Modifications on harmony memory consideration rate have been studied in many researches [30,31]. Through the reference, it can be concluded that harmony memory consideration rate should be given a small value to increase the diversity of the harmony memory and global search when solutions differ greatly.…”

Section: Improvements On Harmony Memory Considerationmentioning

confidence: 99%

“…Parameters are set as follows: ingen = 100, 0 = 0.3, = 5, visual = 1.5, 1 = 0.3, 2 = 0.5, 1 = 0.6, 2 = 0.4, 1 = 0.6, 2 = 0.4, max gen = 100000, and = 30; for other parameters, refer to [24,30,32].…”

Section: Verification Tests By Benchmarkmentioning

confidence: 99%

A New Approach to Weapon-Target Assignment in Cooperative Air Combat

Chang

Kou

et al. 2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

A new approach to solving weapon-target assignment (WTA) problem is proposed in this paper. Firstly, relative superiority that lays the foundation for assignment is calculated based on the combat power energy of the fighters. Based on the relative superiority, WTA problem is formulated. Afterwards, a hybrid algorithm consisting of improved artificial fish swarm algorithm (AFSA) and improved harmony search (HS) is introduced and furthermore applied to solve the assignment formulation. Finally, the proposed approach is validated by eight representative benchmark functions and two concrete cooperative air combat examples. The results show that the approach proposed in this paper achieves good performances in solving WTA problem in cooperative air combat.

show abstract

“…Moreover, it has few mathematical requirements and derivative information is not needed, because it uses the stochastic random search [2][3][4]. The HS has been successfully applied to various areas, including the binary coded optimization problems [5], the reaction kinetic parameter estimation [6], the power economic load dispatch [7], the cost minimization [8], the damage detection [9], the feature selection [10], the machine learning [11], and the classification [12].…”

Section: Introductionmentioning

confidence: 99%

Improved Convergence Behavior by Using Best Solutions to Enhance Harmony Search Algorithm

Maroosi

Muniyandi²

2016

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Harmony search is an emerging meta-heuristic optimization algorithm inspired from music improvisation processes, and able to solve different optimization problems. In the previous studies harmony search is improved by information of the best solution. This increases speed of coverage to the solution but chance of immature coverage to the local optimum increases by this way. Thus, this study uses information from the p of the best solutions to accelerate coverage to optimal solution while avoiding immature coverage. Simulation results show the proposed approach applied for different numerical optimization problems has better performance than previous approaches.

show abstract

An improved adaptive binary Harmony Search algorithm

Cited by 115 publications

References 34 publications

New binary bat algorithm for solving 0–1 knapsack problem

New binary bat algorithm for solving 0–1 knapsack problem

A New Approach to Weapon-Target Assignment in Cooperative Air Combat

Improved Convergence Behavior by Using Best Solutions to Enhance Harmony Search Algorithm

Contact Info

Product

Resources

About