A novel binary multi-swarms fruit fly optimisation algorithm for the 0-1 multidimensional knapsack problem. (31st March 2023)

• Record Type: Journal Article
• Authors: Du, Xin; Zhou, Jiawei; Ni, Youcong; Liu, Wentao; Xiao, Ruliang; Wu, Xiuli
• Is Part Of: International journal of bio-inspired computation. Volume 21:Number 1(2023)
• Page Start: 1
• Page End: 10
• Publication Date: 2023-03-31
• Subjects: fruit fly optimisation -- multidimensional knapsack problem -- binary optimisation; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

To improve solution quality and accelerate convergence speed of traditional fruit fly optimisation algorithm in solving MKP, a novel binary multi-swarm fruit fly optimisation algorithm (bMFOA) is proposed. It comprises four novelties. Firstly, an item frequency tree (IFT) is constructed based on the idea of frequency pattern mining, and a new search strategy is proposed to obtain heuristic information. Secondly, two new heuristic operators of 'ADD' and 'DROP' are designed according to the obtained heuristic knowledge. Thirdly, a multi-swarm cooperation strategy is presented to strengthen the exploitation capability. To prevent algorithm falling into the local optimum prematurely, a swarm location escape strategy is put forward. To verify the efficiency of bMFOA, it is compared with some existing meta-heuristic methods by solving 58 MKPs from ORLIB. The experimental results show that the bMFOA performs better than existing meta-heuristic methods.