Title: Light responsive curve selection for photosynthesis operator of APOA

Authors: Xingjuan Cai; Shujing Fan; Ying Tan

Addresses: Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, 030024, China ' Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, 030024, China ' Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, 030024, China

Abstract: 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.

Keywords: artificial plant optimisation algorithm; APOA; light responsive curve; parabola models; modelling; curve selection; photosynthesis operators; bio-inspired computation; simulation.

DOI: 10.1504/IJBIC.2012.051411

International Journal of Bio-Inspired Computation, 2012 Vol.4 No.6, pp.373 - 379

Received: 05 Nov 2012
Accepted: 05 Nov 2012
Published online: 22 Sep 2014 *

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