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Novel Multiple Time-grid Continuous-time Mathematical Formulation for Short-term Scheduling of Multipurpose Batch
Dan Li1, Nikolaos Rakovitis1, Taicheng Zheng1
1Centre for Process Integration, Department of Chemical Engineering, The University of Manchester, Manchester M13 9PL, U.K.
Industrial & Engineering Chemistry Research
|November 8, 2022
Summary
Novel mixed-integer linear programming models improve batch plant scheduling by reducing event points and computational effort. These models enhance efficiency and achieve superior objective values compared to existing methods.
Area of Science:
- Chemical Engineering
- Operations Research
Background:
- Scheduling multipurpose batch plants is complex due to task sequencing and material transfer.
- Existing unit-specific event-based models can be computationally intensive and require many event points.
Purpose of the Study:
- To develop novel mixed-integer linear programming (MILP) models for scheduling multipurpose batch plants.
- To improve upon existing unit-specific event-based scheduling models.
Main Methods:
- Developed two novel unit-specific event-based MILP models.
- Introduced concepts of direct and indirect material transfer for task alignment.
- Allowed partial batch transfer or holding over multiple event points.
Main Results:
- Proposed models require fewer event points for optimality in many cases.
- No task needed to span multiple event points to reach optimality.
- Achieved up to 67% improvement in objective values compared to existing models.
- Reduced computational effort by at least one order of magnitude.
Conclusions:
- The novel MILP models offer significant improvements in batch plant scheduling efficiency.
- These models provide a more computationally tractable and effective approach to scheduling complex batch processes.
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