Abstract

This paper is motivated by the fact that Effective resource allocation is a vital factor in optimizing production processes in the paint manufacturing industry. This project aim to apply the Hungarian Algorithm in minimizing production time and costs by optimizing worker-task assignments and machine use.  The methodologies used were the combination of structured system analysis and design Methodology (SSADM) with simple calculations via the Hungarian Algorithm, as the most dominated technique for resolving assignment problems, it is used to allocate workers to specific tasks based on skill levels, efficiency, and workload balance. The researcher modelled the assignment problem by describing cost matrices using the parameters such as worker proficiency, task complexity, and production deadlines. Putting the Algorithm into use, the best assignment of workers on tasks is determined, safeguarding minimal idle time and improved efficacy in the production of paint. Additionally, the algorithm is extended to machine allocation, where different production stages such as mixing, grinding, and packaging are assigned to accessible machines based on their ability and operational efficacy. An expected results gotten shows that the application of the Hungarian Algorithm meaningfully improves productivity by dropping delays and proper resource utilization. Thus integrating this algorithm into paint production can lead to better workforce management, reduced operational costs, and higher output adeptness.

Keywords

  • Efficacy
  • Operational
  • Optimizing
  • Minimizing.

References

  1. 1. Annapurna & Yesaswini (2012), Improved Hungarian Algorithm for Unbalanced Assignment Problems. International Journal of Communication Technologies vol.9 No 1. Retrieved from https://ijccts.org/index.php/pub/article/view/135?
  2. 2. Amal P R; Anjumol K S; Unnikrishnan S; Dilip V & George Oommen(2024) , Optimized Selective Assembly using Hungarian Algorithm. Internal journal of innovative science and research. Volume 9 -, Issue 8. Retrieved from https://ijisrt.com/optimized-selective-assembly-using-hungarian-algorithm?utm
  3. 3. Emili Vizuete-Luciano,José M. Merigó Af, Anna M. Gil-Lafuente & Sefa Boria-Reverter (2015): decision making in the assignment process by using the hungarian algorithm with owa operators, Vilnius tech Journals of Technological and Economic Development of Economy.DOI: https://doi.org/10.3846/20294913.2015.1056275.
  4. 4. Güneri, Ö. İ., Durmus, B., & Aydın, D. (2019). Different approaches to solution of the assignment problem using r program. Journal of Mathematics and Statistical Science, 5, 129–145
  5. 5. Jacyna, M., Izdebski, M., Szczepański, E., & Gołda, P. (2018). The task assignment of
  6. 6. vehicles for a production company. Symmetry, 10(11), 1–19. https://doi.org/10.3390/sym10110551
  7. 7. Irsyadi Z. Akbar R. (2022). The Division of Tasks Using the Hungarian Method. Journal of Business and Management Review.
  8. 8. Li, S., Ni, Q., Sun, Y., Min, G., & Al-Rubaye, S. (2018). Energy-Efficient Resource
  9. 9. Allocation for Industrial Cyber-Physical IoT Systems in 5G Era. IEEE Transactions on Industrial Informatics, 14(6), 2618–2628. https://doi.org/10.1109/TII.2018.2799177
  10. 10. Marangoz, S., Amasyalı, M. F., Uslu, E., Çakmak, F., Altuntaş, N., & Yavuz, S. (2019).
  11. 11. More scalable solution for multi-robot–multi-target assignment problem. Robotics and Autonomous Systems, 113, 174–185
  12. 12. Meng zhou , Jianyu,Li, Changwang Weifeng zhai & Vicenc puig (2024) Global Round-up Strategy Based on an Improved Hungarian Algorithm for Multi-robot Systems. Journal of Intelligent & Robotic Systems springer nature Volume 110, article number 168, retrieved from https://link.springer.com/article/10.1007/s10846-024-02190-4?utm.
  13. 13. Tram B.T Tran a, and Hien Hoang Phuoc Nguyen (2023), Optimizing Labor Allocation based on Multiobjective Decision Making Using Improved Hungarian Algorithm, Journals of Economic and Statistics , Anser press Vol. 1 Issue 3 . Retrieved from https://www.anserpress.org/journal/jes/1/3/15? 10.58567/jes01030002.
  14. 14. Sulaimon Olanrewaju, Adebiyi Bilqis, Bolanle Amole & Ismail Oladimeji Soile (2014). Linear
  15. 15. Optimization Techniques for Product-Mix of Paints Production in Nigeria
  16. 16. Acta Universitatis Danubius. Œconomica, Vol 10, No 1 (2014).
  17. 17. wai dei et al., 2019 ,Task Allocation Without Communication Based on Incomplete Information Game Theory for Multi-robot Systems, Journal of Intelligent & Robotic Systems 94(1) ,
  18. https://doi:10.1007/s10846-018-0783-y
  19. 18. Nedlux Paints and Chemical Industries LTD (2015), No 1 Nwachukwu Agbaja Road Felele Lokoja Kogi State Nigeria.
  20. 19. Hungarian Algorithm Steps (2024) , Retrieved from: https://www.hungarianalgorithm.com/hungarianalgorithm.php