Abstract
As manufacturing environments are getting increasingly decentralized, while the customer diversity of requirements is continuously growing, it becomes important for manufacturers to optimize complex production processes across multiple factories. We propose a dynamic algorithm based on a fully polynomial approximation scheme (FPTAS) to schedule jobs between a main factory and another set of sub-factories. The decision maker will balance workload across the two sets of factories, while considering each job’s specific properties such as complexity, due-date, profit earned if completed on time. We validated the algorithm applicability in real life, using data provided by a company that is involved in building development. Our results suggest that our algorithm has the potential to assist decision makers in efficiently assigning jobs across multiple processors. To the best of our knowledge, the current paper is the first to propose and design a rapid and efficient FPTAS approximation for a multi-factory setting.
| Original language | American English |
|---|---|
| Pages (from-to) | 313-320 |
| Number of pages | 8 |
| Journal | Journal of Industrial and Production Engineering |
| Volume | 37 |
| Issue number | 7 |
| DOIs | |
| State | Published - 2 Oct 2020 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Decision making
- FPTAS
- Multi-factory
- scheduling
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
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