arXiv:2608.30419v1 Announce Type: new
Abstract: Healthcare workforce scheduling is an NP-hard optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, emp...
By Vipul Patel, Anirudh Deodhar, Dagnachew Birru
SCHEDBench is a natural‑language benchmark that evaluates whether large language models (LLMs) produce schedules that remain constraint‑feasible when the same scheduling problem is expressed in different natural‑language surface forms. The benchmark covers 1,132 instances from job‑shop scheduling, resource‑constrained project scheduling, nurse rostering, and curriculum timetabling, and uses domain‑specific templates and surface‑form variations to generate varied problem statements. Experiments with thirteen frontier and open‑weight LLMs show that models are not reliably invariant to semantically equivalent renderings, with surface‑form variation reducing feasibility and increasing hard‑constraint violations, especially when constraints are reordered.
By Shrenil Shaun Sharma, Avi Sharma
arXiv:2601. 06542v2 Announce Type: replace-cross Abstract: In this paper, we investigate the Resource-Constrained Project Scheduling Problem (RCPSP) with Time-of-Use (TOU) energy tariffs and machine states, a variant of RCPSP for production scheduling, where energy price is part of the criteria and one highly energy-demanding machine can be in one of the following three states: proc, idle, or off.
By Corentin Juvigny, Anton\'in Nov\'ak, Jan Mand\'ik, Zden\v{e}k Hanz\'alek
arXiv:2508.01751v3 Announce Type: replace
Abstract: Modeling scheduling problems with conditional time intervals and cumulative functions has become a common approach when using modern commercial con...
By Pierre Schaus, Charles Thomas, Roger Kameugne
The paper introduces SDDL, a neuro‑symbolic framework that converts natural‑language combinatorial scheduling problems into compact, solver‑aligned representations, delegating low‑level modeling and search to a deterministic compiler and external solver. On a 300‑instance subset of scheduling tasks, SDDL achieves higher feasibility rates for resource‑constrained language models—up to 55.3% and 28.3%—compared to direct‑generation baselines (23.7% and 1.3%) and solver‑code baselines (21.7% and 7.0%), with a median optimality gap of 0.0% among feasible schedules.
By Shrenil Shaun Sharma, Avi Sharma
arXiv:2607. 11725v1 Announce Type: cross Abstract: Prefabricated prefinished volumetric construction moves most building work into module factories, whose production floor operates as a flexible job shop.
By Ziheng Zhang, Wei Zhang