Optimized Parameter Settings of Binary Bat Algorithm for Solving Function Optimization Problems

• Published in: Journal of Electrical and Computer Engineering Vol. 2018; no. 2018; pp. 1 - 9
• Main Authors: Ma, Xiao-Xu, Wang, Jie-sheng
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018; Hindawi; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Bats; Bionics; Cloud computing; Computer simulation; Convergence; Dictionaries; Echolocation (Physiology); Fault diagnosis; Foraging behavior; Information science; Loudness; Mathematical optimization; Optimization; Optimization algorithms; Parameter sensitivity; Pulse rate; Remote sensing; Searching; Sound waves; Velocity; Wind power
• ISSN: 2090-0147; 2090-0155; 2090-0155
• DOI: 10.1155/2018/3847951

The bat algorithm (BA) is a new bionic intelligent optimization algorithm to simulate the foraging behavior and the echolocation principle of the bats. The parameter initialization of the discussed binary bat algorithm (BBA) has important influence on the convergence speed, convergence precision, and good global searching ability of the BBA. The convergence speed and algorithm searching precision are determined by the pulse of loudness and pulse rate. The simulation experiments are carried out by using the six typical test functions to discuss this influence. The simulation results show that the convergence speed of the BBA is relatively sensitive to the setting of the algorithm parameters. The convergence precision reduces when increasing the rate of bat transmitted pulse alone and the convergence speed increases the launch loudness alone. The proper combination of BBA parameters (the rate of bat transmitted pulse and the launch loudness) can flexibly improve the algorithm’s convergence velocity and improve the accuracy of the searched solutions.