Bacterial colony foraging for multi-mode product colour planning

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.

[1]  Zhihua Cui,et al.  PID-Controlled Particle Swarm Optimization , 2010, J. Multiple Valued Log. Soft Comput..

[2]  W. Hsu,et al.  Color selection in the consideration of color harmony for interior design , 2000 .

[3]  C. N. Bhende,et al.  Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation , 2007, IEEE Transactions on Power Delivery.

[4]  Dong Hwa Kim,et al.  Adaptive Tuning of PID Controller for Multivariable System Using Bacterial Foraging Based Optimization , 2005, AWIC.

[5]  B. Bassler,et al.  Quorum sensing in bacteria. , 2001, Annual review of microbiology.

[6]  Ying Tan,et al.  Light responsive curve selection for photosynthesis operator of APOA , 2012, Int. J. Bio Inspired Comput..

[7]  P. Lakshmi,et al.  Particle swarm optimisation applied to real time control of spherical tank system , 2012, Int. J. Bio Inspired Comput..

[8]  Hung-Cheng Tsai,et al.  Computer Aided Product Color Design with Artificial Intelligence , 2007 .

[9]  H. Levine,et al.  Bacterial linguistic communication and social intelligence. , 2004, Trends in microbiology.

[10]  James A. Shapiro,et al.  BACTERIA AS MULTICELLULAR ORGANISMS , 1988 .

[11]  Sukumar Mishra,et al.  A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation , 2005, IEEE Transactions on Evolutionary Computation.

[12]  Yichuan Shao,et al.  Cooperative Bacterial Foraging Optimization , 2009, 2009 International Conference on Future BioMedical Information Engineering (FBIE).

[13]  Hanning Chen,et al.  Adaptive Bacterial Foraging Optimization , 2011 .

[14]  M. Ulagammai,et al.  Application of bacterial foraging technique trained artificial and wavelet neural networks in load forecasting , 2007, Neurocomputing.

[15]  Ajith Abraham,et al.  Adaptive Computational Chemotaxis in Bacterial Foraging Optimization: An Analysis , 2009, IEEE Transactions on Evolutionary Computation.

[16]  Petros Koumoutsakos,et al.  Optimization based on bacterial chemotaxis , 2002, IEEE Trans. Evol. Comput..

[17]  Shih-Wen Hsiao,et al.  Use of gray system theory in product‐color planning , 2004 .

[18]  L. Giraldeau,et al.  Food exploitation: searching for the optimal joining policy. , 1999, Trends in ecology & evolution.

[19]  Min-Yuan Ma,et al.  A design decision-making support model for customized product color combination , 2007, Comput. Ind..

[20]  Shih-Wen Hsiao,et al.  An image evaluation approach for parameter-based product form and color design , 2006, Comput. Aided Des..

[21]  Hung-Cheng Tsai,et al.  Automatic Product Color Design Using Genetic Searching , 2007 .

[22]  Zhihua Cui,et al.  Integral Particle Swarm Optimization with Dispersed Accelerator Information , 2009, Fundam. Informaticae.

[23]  Xiaodong Li,et al.  Particle Swarms for Dynamic Optimization Problems , 2008, Swarm Intelligence.

[24]  Clarence Rainwater Light and Color , 1982 .

[25]  Sukumar Mishra,et al.  Transmission Loss Reduction Based on FACTS and Bacteria Foraging Algorithm , 2006, PPSN.

[26]  Chung-Hsing Yeh,et al.  User-oriented design for the optimal combination on product design , 2006 .

[27]  Yunlong Zhu,et al.  Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning , 2010, Appl. Soft Comput..

[28]  S. Sumathi,et al.  Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab , 2008 .

[29]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[30]  S. Mishra Bacteria foraging based solution to optimize both real power loss and voltage stability limit , 2007, 2007 IEEE Power Engineering Society General Meeting.

[31]  J. Adler Chemotaxis in Bacteria , 1966, Science.

[32]  Jyh-Rong Chou,et al.  Automatic design support and image evaluation of two-coloured products using colour association and colour harmony scales and genetic algorithm , 2007, Comput. Aided Des..