A self-adaptive multi-objective harmony search algorithm based on harmony memory variance

2015 ◽  
Vol 35 ◽  
pp. 541-557 ◽  
Author(s):  
Xiangshan Dai ◽  
Xiaofang Yuan ◽  
Zhenjun Zhang
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Multi Objective ◽  
Harmony Memory ◽  
Self Adaptive

Semi-self-adaptive harmony search algorithm

2017 ◽  
Vol 16 (4) ◽  
pp. 619-636 ◽  
Author(s):  
Xinchao Zhao ◽  
Zhaohua Liu ◽  
Junling Hao ◽  
Rui Li ◽  
Xingquan Zuo
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Self Adaptive

Modified Harmony Search Algorithm for 0-1 Knapsack Problems

2013 ◽  
Vol 365-366 ◽  
pp. 182-185
Author(s):  
Hong Gang Xia ◽  
Qing Liang Wang
Keyword(s):  
Convergence Rate ◽  
Objective Function ◽  
Objective Function Value ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Knapsack Problems ◽  
Convergence And Stability ◽  
Update Strategy ◽  
Harmony Memory

In this paper, a modified harmony search (MHS) algorithm was presented for solving 0-1 knapsack problems. MHS employs position update strategy for generating new solution vectors that enhances accuracy and convergence rate of harmony search (HS) algorithm. Besides, the harmony memory consideration rate (HMCR) is dynamically adapted to the changing of objective function value in the current harmony memory, and the key parameters PAR and BW dynamically adjusted with the number of generation. Based on the experiment of solving ten classic 0-1 knapsack problems, the MHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its two improved algorithms (IHS and NGHS).

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