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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 10

Published on: October 2026

A HYBRID MULTI-OBJECTIVE COLOUR RECOMMENDATION FRAMEWORK FOR INTERIOR WALL PAINTING USING NSGA-II AND RETAIL SERVICE INTEGRATION

Amit Rampratap Vishwakarma Vivek Kumar Sahni Tattapure Shantling Bhimashankar

Prof. Anjali Yeldi

ASM’s Institute of Business Management and Research, Pune, Maharashtra, India
DOI:https://doi.org/10.55041/ijcope.v2i10.058

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Abstract

Selecting interior wall paint involves multiple conflicting objectives such as aesthetic colour harmony, material cost, and vendor reliability. Traditional e-commerce platforms offer fragmented services and lack integrated visualization or professional painter booking. Earlier research works mainly focused on Interactive Genetic Algorithms and automated material suggestion for 3D indoor scenes, but they did not combine colour optimization with real-world retail logistics and on-demand labour services. This paper presents a hybrid Multi-Objective Colour Recommendation System that bridges this gap. The proposed system integrates a Zomato-style paint delivery model, an Urban Company-style painter booking model, and a Policy Bazaar-style multi-brand comparison approach. Using K-Means clustering for dominant colour extraction from room photographs and NSGA-II for multi-objective optimization, the system generates Pareto-optimal recommendations that simultaneously balance colour harmony, cost, and vendor reliability.

Keywords: Multi-Objective Optimization, NSGA-II, K-Means Clustering, Colour Recommendation, E-Commerce Integration, Pareto Front.

How to Cite this Paper

Vishwakarma, A. R., Sahni, V. K. & Bhimashankar, T. S. (2026). A Hybrid Multi-Objective Colour Recommendation Framework for Interior Wall Painting Using NSGA-II and Retail Service Integration. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(10), 1-9. https://doi.org/10.55041/ijcope.v2i10.058

Vishwakarma, Amit, et al.. "A Hybrid Multi-Objective Colour Recommendation Framework for Interior Wall Painting Using NSGA-II and Retail Service Integration." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i10.058.

Vishwakarma, Amit,Vivek Sahni, and Tattapure Bhimashankar. "A Hybrid Multi-Objective Colour Recommendation Framework for Interior Wall Painting Using NSGA-II and Retail Service Integration." International Journal of Creative and Open Research in Engineering and Management 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i10.058.

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References

[1] W. Huang and W. Xu, “Interior colour preference investigation using interactive genetic algorithm,” Journal of Asian Architecture and Building Engineering, vol. 8, no. 2, pp. 439–445, 2009.

[2] K. Chen et al., “Magic Decorator: Automatic material suggestion for indoor digital scenes,” ACM Transactions on Graphics, vol. 34, no. 6, 2015.

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[5] L. Xue and C. He, “Application of modern architectural colour layout in interior design,” 2023.

[6] H. Zhang et al., “Interactive interior design recommendation via coarse-to-fine multimodal reinforcement learning,” Proc. ACM MM, 2023.

[7] K. Deb et al., “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, 2002.

[8] M. R. Luo, G. Cui and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE2000,” Colour Research & Application, 2001.

Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
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  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Oct 10 2026
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