Solving an Optimization Problem of Image View Layout with Priority using Heuristic Approach
DOI:
https://doi.org/10.38043/tiers.v6i1.6519Keywords:
Greedy Approach, Image View Layout with Priority, Swarm Optimization, User InterfaceAbstract
The image view layout with priority (IVLP) problem focuses on efficiently arranging picture cards of uniform height but varying widths into the minimum number of 2D frames or display sets and prioritizing images with higher priority to be placed at the earlier displays. We mathematically modeled IVLP using integer linear programming. To approximate IVLP solutions, we introduce a greedy-based heuristic, Best-Fit-IVLP (BFI), and a swarm optimization algorithm, Ant Colony Optimization (ACO). BFI allocates picture cards in descending order of priority and width for each display line, seeking another card that can optimally fill the remaining space on each line. In contrast, ACO randomly arranges cards from high to low priority within every line. Experimental results using different numbers of SVG images indicate that BFI and ACO generate solutions close to optimal. BFI demonstrates superior practicality, executing significantly faster than ACO; for 160 images, BFI runs in 0.00044 seconds compared to ACO's 117.93 seconds. Both BFI and ACO achieve space utility rates ranging from 0.578 to 0.8. While BFI consistently produces the same card arrangement, ACO offers diverse arrangements for identical optimal display set counts and space utilization.
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M. Rezae, N. Chen, D. McMeekin, T. Tan, A. Krishna, and H. Lee, The evaluation of a mobile user interface for people on the autism spectrum: An eye movement study, Int J Hum Comput Stud, vol. 142, p. 102462, Oct. 2020, doi: 10.1016/j.ijhcs.2020.102462.
M. Alzahrani, A. L. Uitdenbogerd, and M. Spichkova, Human-Computer Interaction: Influences on Autistic Users, Procedia Comput Sci, vol. 192, pp. 46914700, 2021, doi: 10.1016/j.procs.2021.09.247.
Cboard, Cboard: Communication for Everyone. Accessed: Mar. 19, 2024. [Online]. Available: https://www.cboard.io/
Dream Oriented, Leeloo AAC - Austim Speech App. Accessed: Jul. 01, 2023. [Online]. Available: https://play.google.com/store/apps/details?id=org.dreamoriented.leeloo&hl=en-ID&pli=1
H. Hersinta, C. R. A. Bangun, and O. D. Hutagaol, Developing VICARA 2.0: Exploring the potential use of augmentative and alternative communication (AAC) apps for the parents and teachers of autistic students, in AIP Conference Proceedings, AIP Publishing., 2023. doi: 10.1063/5.0127048.
Vicara 2, Google Play. Accessed: Jul. 02, 2025. [Online]. Available: https://play.google.com/store/apps/details?id=com.vicara.vicara2
L. Hiryanto, A. Putra Wirawan, and Tony, Greedy Approach for Optimizing Image View Layout on Various Sizes of 2D UI Container, in 2024 International Conference on Electrical Engineering and Computer Science (ICECOS), IEEE, Sep. 2024, pp. 298303. doi: 10.1109/ICECOS63900.2024.10791081.
M. Iori, V. L. de Lima, S. Martello, F. K. Miyazawa, and M. Monaci, Exact solution techniques for two-dimensional cutting and packing, Eur J Oper Res, vol. 289, no. 2, pp. 399415, Mar. 2021, doi: 10.1016/j.ejor.2020.06.050.
S. Polyakovskiy and R. MHallah, Just-in-time two-dimensional bin packing, Omega (Westport), vol. 102, p. 102311, Jul. 2021, doi: 10.1016/j.omega.2020.102311.
C. Liu, K. Smith-Miles, T. Wauters, and A. M. Costa, Instance space analysis for 2D bin packing mathematical models, Eur J Oper Res, vol. 315, no. 2, pp. 484498, Jun. 2024, doi: 10.1016/j.ejor.2023.12.008.
A. M. Chwatal and S. Pirkwieser, Solving the Two-Dimensional Bin-Packing Problem with Variable Bin Sizes by Greedy Randomized Adaptive Search Procedures and Variable Neighborhood Search, 2012, pp. 456463. doi: 10.1007/978-3-642-27549-4_58.
H. Zhang, Q. Liu, L. Wei, J. Zeng, J. Leng, and D. Yan, An iteratively doubling local search for the two-dimensional irregular bin packing problem with limited rotations, Comput Oper Res, vol. 137, p. 105550, Jan. 2022, doi: 10.1016/j.cor.2021.105550.
Y. Yuan, K. Tole, F. Ni, K. He, Z. Xiong, and J. Liu, Adaptive simulated annealing with greedy search for the circle bin packing problem, Comput Oper Res, vol. 144, p. 105826, Aug. 2022, doi: 10.1016/j.cor.2022.105826.
S. Kosari, M. Hosseini Shirvani, N. Khaledian, and D. Javaheri, A Hybrid Discrete Grey Wolf Optimization Algorithm Imbalance-ness Aware for Solving Two-dimensional Bin-packing Problems, J Grid Comput, vol. 22, no. 2, p. 49, Jun. 2024, doi: 10.1007/s10723-024-09761-7.
W. Chen, H. Yu, X. Li, L. Qu, and Z. Mi, Layout Design with a Firefly Algorithm for User Interfaces in Vehicle System, in 2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE), IEEE, Sep. 2020, pp. 110113. doi: 10.1109/ICISCAE51034.2020.9236921.
X. Zhang, M. Shan, and J. Zeng, Parallel Batch Processing Machine Scheduling Under Two-Dimensional Bin-Packing Constraints, IEEE Trans Reliab, vol. 72, no. 3, pp. 12651275, Sep. 2023, doi: 10.1109/TR.2022.3201333.
K. Zhu, N. Ji, and X. D. Li, Hybrid Heuristic Algorithm Based On Improved Rules & Reinforcement Learning for 2D Strip Packing Problem, IEEE Access, vol. 8, pp. 226784226796, 2020, doi: 10.1109/ACCESS.2020.3045905.
P. Duan, C. Wierzynski, and L. Nachman, Optimizing User Interface Layouts via Gradient Descent, in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, New York, NY, USA: ACM, Apr. 2020, pp. 112. doi: 10.1145/3313831.3376589.
M. Kaleta and T. liwiski, Neural-Driven Constructive Heuristic for 2D Robotic Bin Packing Problem, Electronics (Basel), vol. 14, no. 10, p. 1956, May 2025, doi: 10.3390/electronics14101956.
M. Bertucco and T. D. Sanger, A Model to Estimate the Optimal Layout for Assistive Communication Touchscreen Devices in Children With Dyskinetic Cerebral Palsy, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 7, pp. 13711380, Jul. 2018, doi: 10.1109/TNSRE.2018.2840445.
K. Fukaya, D. Daylamani-Zad, and H. Agius, Intelligent Generation of Graphical Game Assets: A Conceptual Framework and Systematic Review of the State of the Art, ACM Comput Surv, vol. 57, no. 5, pp. 138, May 2025, doi: 10.1145/3708499.
Z. Fan, B. Ghaddar, X. Wang, L. Xing, Y. Zhang, and Z. Zhou, Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process, Jan. 2024.
D. Knop, M. Pilipczuk, and M. Wrochna, Tight Complexity Lower Bounds for Integer Linear Programming with Few Constraints, ACM Transactions on Computation Theory, vol. 12, no. 3, pp. 119, Sep. 2020, doi: 10.1145/3397484.
B. Guo et al., Two-dimensional irregular packing problems: A review, Front Mech Eng, vol. 8, Aug. 2022, doi: 10.3389/fmech.2022.966691.
J. Zeng and X. Zhang, An Adaptive Large Neighborhood Search for Single-Machine Batch Processing Scheduling With 2-D Rectangular Bin-Packing Constraints, IEEE Trans Reliab, vol. 71, no. 1, pp. 139148, Mar. 2022, doi: 10.1109/TR.2021.3128167.
H. Zhao, C. Zhu, X. Xu, H. Huang, and K. Xu, Learning practically feasible policies for online 3D bin packing, Science China Information Sciences, vol. 65, no. 1, p. 112105, Jan. 2022, doi: 10.1007/s11432-021-3348-6.
M. Witteman, Q. Deng, and B. F. Santos, A bin packing approach to solve the aircraft maintenance task allocation problem, Eur J Oper Res, vol. 294, no. 1, pp. 365376, Oct. 2021, doi: 10.1016/j.ejor.2021.01.027.
M. Dorigo and T. Sttzle, Ant Colony Optimization: Overview and Recent Advances, 2019, pp. 311351. doi: 10.1007/978-3-319-91086-4_10.
R. Priyadarshi and R. R. Kumar, Evolution of Swarm Intelligence: A Systematic Review of Particle Swarm and Ant Colony Optimization Approaches in Modern Research, Archives of Computational Methods in Engineering, Mar. 2025, doi: 10.1007/s11831-025-10247-2.
G. Li, C. Liu, L. Wu, and W. Xiao, A mixing algorithm of ACO and ABC for solving path planning of mobile robot, Appl Soft Comput, vol. 148, p. 110868, Nov. 2023, doi: 10.1016/j.asoc.2023.110868.
Jerry Yurchisin, Getting Started with Mathematical Optimization in Python, gurobi.com. Accessed: Jul. 02, 2025. [Online]. Available: https://www.gurobi.com/resources/mathematical-optimization-in-python-how-to-get-started/
Vicara 3, play.google.com. Accessed: Jul. 02, 2025. [Online]. Available: https://play.google.com/store/apps/details?id=com.vicaraxebp.vicara3&hl=id
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