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Applying Mathematical Modeling Optimization Algorithms to Solve Shop Floor Scheduling Problems

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Yayımlandı:Informatica vol. 49, no. 19 (May 2025), p. 127-143
Yazar: Lv, Xing
Diğer Yazarlar: Chang, Hejie
Baskı/Yayın Bilgisi:
Slovenian Society Informatika / Slovensko drustvo Informatika
Konular:
Scheduling
Mathematical models
Genetic algorithms
Optimization
Productivity
Algorithms
Job shops
Sequences
Manufacturing
Simulated annealing
Heuristic
Neighborhoods
Optimization algorithms
Materials handling
Efficiency
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Özet:Shop floor scheduling is a key optimization problem in contemporary manufacturing, seeking to enhance production tasks and resources while increasing productivity and lowering costs. This paper solves the shop floor scheduling problem using an extensive mathematical model and an enhanced simulated annealing (SA) algorithm. The mathematical model captures intricate aspects such as machine allocation, job sequencing, batch transportation, and assembly procedures. To effectively solve the issue, the enhanced SA algorithm employs significant enhancement tactics like knowledge - driven initialization, a problem-specific neighborhood structure, and a restart mechanism to improve solution quality. The methodology is validated using an extensive experimental setup that investigates different situations with varying machine counts and job intricacies. Key findings show a 25% average decrease in makespan, a 20% rise in scheduling effectiveness, and a 15% reduction in computation time, demonstrating the algorithm's efficiency. These results highlight the theoretical and practical importance of this method in tackling real-world shop floor scheduling issues.
ISSN:0350-5596
1854-3871
DOI:10.31449/inf.v49119.7113
Kaynak:Advanced Technologies & Aerospace Database