New inspirations in swarm intelligence: a survey
International Journal of Bio-Inspired Computation
Review of meta-heuristics and generalised evolutionary walk algorithm
International Journal of Bio-Inspired Computation
Modified biogeography-based optimisation (MBBO)
International Journal of Bio-Inspired Computation
International Journal of Wireless and Mobile Computing
Training artificial neural networks using APPM
International Journal of Wireless and Mobile Computing
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
A new stochastic algorithm to direct orbits of chaotic systems
International Journal of Computer Applications in Technology
Social emotional optimisation algorithm with emotional model
International Journal of Computational Science and Engineering
APOA with parabola model for directing orbits of chaotic systems
International Journal of Bio-Inspired Computation
A new design method using opposition-based BAT algorithm for IIR system identification problem
International Journal of Bio-Inspired Computation
Artificial plant optimisation algorithm with three-period photosynthesis
International Journal of Bio-Inspired Computation
Group search optimiser: a brief survey
International Journal of Computing Science and Mathematics
Using APPM-trained ANN to solve stochastic expected value mode
International Journal of Bio-Inspired Computation
Hybrid ABC/PSO to solve travelling salesman problem
International Journal of Computing Science and Mathematics
Bio-inspired computation: success and challenges of IJBIC
International Journal of Bio-Inspired Computation
Ant colony optimisation for vehicle traffic systems: applications and challenges
International Journal of Bio-Inspired Computation
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Artificial plant optimisation algorithm (APOA) is a recent proposed evolutionary computation methodology in which the growing process of one tree is mapped into the optimised problem. In APOA, three new operators: photosynthesis operator, phototropism operator and apical dominance operator are designed to simulate three important phenomenon. In the standard version of APOA, the light responsive curve of photosynthesis operator is selected as rectangular hyperbolic model which is only a general one. However, we argue whether the rectangular hyperbolic model provide the best average performance? In this paper, seven classical models are chosen to investigate, they are: rectangular hyperbolic model, non-rectangular hyperbolic model, updated rectangular hyperbolic model, parabola model, straight line model and two exponential curve models. To test the performance, eleven benchmarks are selected. In each experiment, the light responsive curve is translated by the corresponding model. Simulation results show the average performance of parabola model is best when compared with other six models.