1222. Distributed Permutation Flowshop Scheduling with Tool Transfers: A Novel Approach to Minimize Total Tardiness
Invited abstract in session MD-12: Flow shop scheduling and line balancing, stream Scheduling and Project Management.
Monday, 14:30-16:00Room: Clarendon SR 1.02
Authors (first author is the speaker)
| 1. | Martin Schönheit
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| Chair of Business Administration, esp. Logistics, TU Dresden | |
| 2. | Tristan Becker
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| TU Dresden | |
| 3. | Rainer Lasch
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| Fakultät Wirtschaftswissenschaften, Lehrstuhl für BWL, insb. Logistik, Technische Universität Dresden |
Abstract
The increasing frequency of supply chain disruptions due to climate change and political conflicts highlights supply chain vulnerabilities. To mitigate risks, companies diversify production sites, giving rise to the distributed permutation flow shop scheduling problem (DPFSP). In many industries, machines need specialized tools to process specific jobs, creating eligibility constraints. These tools can be cost-intensive or highly specialized, making full redundancy across factories impractical. Therefore, we extend the DFSP by tool availability with the possibility of transferring tools between factories. Transferring tools can enable job processing at otherwise ineligible factories, potentially offering economic and environmental advantages over transporting final products over long distances. To capture the impact of factory location on the assignment of jobs, we minimize total tardiness while considering factory-dependent due dates. In this context, we evaluate the benefits of tool transfers by proposing a network flow-based mixed-integer programming model, a constraint programming formulation, and an iterated greedy algorithm. Through extensive computational experiments, we demonstrate that tool transfers can effectively reduce total tardiness, while also assessing the impact of varying levels of tool redundancy on its minimization.
Keywords
- Scheduling
- Metaheuristics
Status: accepted
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