Bacterial colony foraging for multi-mode product colour planning. (2015)

• Record Type: Journal Article
• Authors: Chen, Hanning; Zhu, Yunlong; Ma, Lianbo; Su, Weixing
• Is Part Of: International journal of bio-inspired computation. Volume 7:Number 4(2015)
• Page Start: 240
• Page End: 262
• Publication Date: 2015
• Subjects: colour planning -- multimode products -- MMP -- bacterial foraging -- bacterial chemotaxis -- cell-to-cell communication -- self-adaptive foraging strategy -- bacterial colony foraging -- BCF -- product colours -- product development -- product design -- evaluation modelling -- colour combinations -- genetic algorithms -- GAs -- particle swarm optimisation -- PSO -- hair dryers -- working modes -- simulation; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

In this work, in order to assist designer in colour planning during product development, an efficient synthesised evaluation model is presented to evaluate colour-combination schemes of multi-working modes products (MMP). A novel bacterial colony foraging (BCF) algorithm is proposed to search for the optimal colour-combination schemes of MMP based on the evaluation model. The proposed BCF extend original bacterial foraging algorithm to adaptive and cooperative mode by combining bacterial chemotaxis, cell-to-cell communication, and a self-adaptive foraging strategy. The experiment presents an exhaustive comparison of the proposed BCF and two successful bio-inspired search techniques, namely the genetic algorithm (GA) and particle swarm optimisation (PSO), on three MMP tested cases of different nature, namely a hair-drier with two-coloured areas and two working modes, and two arm-type aerial work platforms both two-coloured products while with two and three working modes, respectively. Simulation results demonstrate that the proposed method is feasible and efficient.