Hybrid Atomic Orbital Search Optimization Algorithm Improves Scheduling Performance

Strategic Insights -

Researchers at Mepco Schlenk Engineering College have developed a new optimization technique that utilizes atomic orbitals to address issues in hybrid flow shop (HFS) scheduling. The proposed algorithm, known as hybrid atomic orbital search optimization algorithm (HAOSOA), is designed to minimize makespan and improve productivity and resource utilization in the electrical panel board manufacturing industry. The algorithm was tested on a variety of random test situations and benchmark problems, and the results showed that it outperforms well-known algorithms in the literature.

Key Takeaways:

  • The HAOSOA algorithm is designed to address the complex and NP-hard problem of HFS scheduling in manufacturing and service industries.
  • The algorithm utilizes atomic orbitals to enhance solution quality and minimizes makespan, which is critical for improving productivity and resource utilization.
  • The HAOSOA algorithm was tested on a variety of random test situations and benchmark problems, and the results showed that it outperforms well-known algorithms in the literature.
  • The algorithm was able to find the best makespan for 65 of the 77 problems in the second test.
  • The performance of the proposed algorithm was evaluated using the Friedman and Wilcoxon test, which indicated that it improves solution quality in each test instance compared to all the metaheuristics used for comparison.
  • The proposed algorithm was compared against well-known algorithms discussed in the literature, including metaheuristics used for comparison.
  • The research concluded that the HAOSOA algorithm is a viable solution for solving the scheduling problem in the electrical panel board manufacturing industry.

Statistics:

  • 65 of the 77 problems were solved with the best makespan using the HAOSOA algorithm in the second test.
  • The HAOSOA algorithm outperformed all the metaheuristics used for comparison in each test instance.
  • The proposed algorithm was tested on a variety of random test situations of varying sizes and configurations.

Sources:

  • NewsRx. Study Results from Mepco Schlenk Engineering College Provide New Insights into Technology (Solving the Scheduling Problem In the Electrical Panel Board Manufacturing Industry Using a Hybrid Atomic Orbital Search Optimization Algorithm). Mathematics Week. October 21, 2025; p 491.
  • Mdpi. Processes. 2025;13(9):2930.
  • Mepco Schlenk Engineering College, Dept. of Mechanical Engineering, Sivakasi 626005, Tamilnadu, India.