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Scheduling Seminar Series Talk #82: Debiao Li - Feature-driven Robust Stochastic Scheduling for Printed Circuit Board Assembly, May 13, 2026 15:00-16:30 CET

• Objective of a virtual seminar on scheduling research and applications is to discuss both the field's newest advancements and survey traditional areas. Seminars take place typically on every second Wednesday through three different time zones (Europe, the Middle East & Africa, North America & South America, and Asia, Australia & Oceania).
  
  More information about the Scheduling Seminar can be found here: https://schedulingseminar.com/
  
  

  Upcoming Talk:
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  13 May, 15:00–16:30 CET

  Presenter: Debiao Li - Feature-driven Robust Stochastic Scheduling for Printed Circuit Board Assembly

  Abstract:
  
  

  Motivated by an industry project, this talk addresses scheduling in printed circuit board assembly (PCBA), a bottleneck of electronic manufacturing. We consider uncertain processing and setup times arising from machine variability and human intervention, and model the problem as identical parallel machine scheduling to minimize total completion time and makespan. We develop a feature-driven robust stochastic optimization model that embeds production features into decision-making: processing times are predicted via support vector regression, while setup uncertainty is captured through event-wise ambiguity sets constructed by K-means clustering. The model is reformulated as a mixed-integer linear program and solved using a branch-and-price (B&P) algorithm. Experiments on real-world data show that the proposed approach outperforms sample average approximation (SAA) and standard distributionally robust optimization (DRO) by 52% and 33%, respectively. The B&P algorithm scales well to realistic instances, and sensitivity analysis reveals the impact of setup scenarios on the trade-off between solution quality and computational effort.
  
  Invited by: Michael Pinedo (UC Davis)

  
  You can watch the talk online at: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A/live

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  10 June, 15:00–16:30 CET

  Presenter: Danny Segev - New Approximation Guarantees for The Inventory Staggering Problem

  Abstract:
  
  

  Since its inception in the mid-60s, the inventory staggering problem has been explored and exploited in a wide range of application domains, such as production planning, stock control systems, warehousing, and aerospace/defense logistics. However, even with a rich history of academic focus, we are still very much in the dark when it comes to cornerstone computational questions around inventory staggering and to related structural characterizations, with our methodological toolbox being severely under-stocked.

  The central contribution of this paper consists in devising a host of algorithmic techniques and analytical ideas — some being entirely novel and some leveraging well-studied concepts in combinatorics and number theory — for surpassing essentially all known approximation guarantees for the inventory staggering problem. In particular, our work demonstrates that numerous structural properties open the door for designing polynomial-time approximation schemes; these findings offer substantial improvements over currently available constant-factor approximations and resolve outstanding open questions in their respective contexts (Teo et al., 1998; Hum et al., 2005; Hochbaum and Rao, 2019, 2020).

  In parallel, we develop new theory around a number of yet-uncharted questions, related to the sampling complexity of peak inventory estimation as well as to the plausibility of groupwise synchronization.

  
  You can watch the talk online at: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A/live

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  24 June, 15:00–16:30 CET
  
  

  Presenter: Florian Jaehn - Scheduling with restrictions on job positions

  
  

  Abstract:
  
  

  Unlike time restrictions on jobs, such as release dates or deadlines, which are common in scheduling, we consider position restrictions. For example, a job may be required to be in position x of the job sequence. Such a restriction may be motivated by maintenance scheduling, among other things. In maintenance scheduling, we may also encounter constraints, such as a maintenance operation that must be performed after executing at most k jobs.

  We provide an overview of classical one-machine problems and demonstrate how these additional constraints affect their complexity. While the complexity remains unchanged for many cases, it changes for some, revealing surprising effects.

  
  You can watch the talk online at: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A/live
  Posted on 2026-05-03 by Magdalena Sroczan