ArticleSLAS technology2021
Optimal Scheduling for Laboratory Automation of Life Science Experiments with Time Constraints.
Article in SLAS technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Closing the loop: establishing an autonomous test-learn cycle to optimize induction of bacterial systems using a robotic platform.Frontiers in bioengineering and biotechnology · 2024Article
- Machine Learning in Unmanned Systems for Chemical Synthesis.Molecules (Basel, Switzerland) · 2023Review
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Authors and funding
5 authors.
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Abstract
In automated laboratories consisting of multiple different types of instruments, scheduling algorithms are useful for determining the optimal allocations of instruments to minimize the time required to complete experimental procedures. However, previous studies on scheduling algorithms for laboratory automation have not emphasized the time constraints by mutual boundaries (TCMBs) among operations, which is important in procedures involving live cells or unstable biomolecules. Here, we define the "scheduling for laboratory automation in biology" (S-LAB) problem as a scheduling problem for automated laboratories in which operations with TCMBs are performed by multiple different instruments. We formulate an S-LAB problem as a mixed-integer programming (MIP) problem and propose a scheduling method using the branch-and-bound algorithm. Simulations show that our method can find the optimal schedules of S-LAB problems that minimize overall execution time while satisfying the TCMBs. Furthermore, we propose the use of our scheduling method for the simulation-based design of job definitions and laboratory configurations.
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