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A study on constraint extraction and exception exclusion in care worker scheduling

Koki Suenaga, Tomohiro Furuta, Satoshi Ono

TL;DR

The paper tackles care worker rostering in long-term facilities by learning facility-specific constraints from historical rosters using constraint templates, while explicitly excluding exceptional patterns via staffing margin and flexibility. The approach combines constraint extraction with a constraint programming–based scheduler, applying gradual relaxation when hard constraints prove infeasible. Key contributions include a formalization of constraint templates, mechanisms to omit problematic patterns, and an evaluation showing zero hard-constraint violations and reduced soft-constraint violations compared to baselines. The method lowers interview burden, preserves schedule feasibility, and improves accommodation of staff preferences, with practical impact for facility-specific rostering systems.

Abstract

Technologies for automatically generating work schedules have been extensively studied; however, in long-term care facilities, the conditions vary between facilities, making it essential to interview the managers who create shift schedules to design facility-specific constraint conditions. The proposed method utilizes constraint templates to extract combinations of various components, such as shift patterns for consecutive days or staff combinations. The templates can extract a variety of constraints by changing the number of days and the number of staff members to focus on and changing the extraction focus to patterns or frequency. In addition, unlike existing constraint extraction techniques, this study incorporates mechanisms to exclude exceptional constraints. The extracted constraints can be employed by a constraint programming solver to create care worker schedules. Experiments demonstrated that our proposed method successfully created schedules that satisfied all hard constraints and reduced the number of violations for soft constraints by circumventing the extraction of exceptional constraints.

A study on constraint extraction and exception exclusion in care worker scheduling

TL;DR

The paper tackles care worker rostering in long-term facilities by learning facility-specific constraints from historical rosters using constraint templates, while explicitly excluding exceptional patterns via staffing margin and flexibility. The approach combines constraint extraction with a constraint programming–based scheduler, applying gradual relaxation when hard constraints prove infeasible. Key contributions include a formalization of constraint templates, mechanisms to omit problematic patterns, and an evaluation showing zero hard-constraint violations and reduced soft-constraint violations compared to baselines. The method lowers interview burden, preserves schedule feasibility, and improves accommodation of staff preferences, with practical impact for facility-specific rostering systems.

Abstract

Technologies for automatically generating work schedules have been extensively studied; however, in long-term care facilities, the conditions vary between facilities, making it essential to interview the managers who create shift schedules to design facility-specific constraint conditions. The proposed method utilizes constraint templates to extract combinations of various components, such as shift patterns for consecutive days or staff combinations. The templates can extract a variety of constraints by changing the number of days and the number of staff members to focus on and changing the extraction focus to patterns or frequency. In addition, unlike existing constraint extraction techniques, this study incorporates mechanisms to exclude exceptional constraints. The extracted constraints can be employed by a constraint programming solver to create care worker schedules. Experiments demonstrated that our proposed method successfully created schedules that satisfied all hard constraints and reduced the number of violations for soft constraints by circumventing the extraction of exceptional constraints.
Paper Structure (16 sections, 4 equations, 7 figures, 3 tables, 5 algorithms)

This paper contains 16 sections, 4 equations, 7 figures, 3 tables, 5 algorithms.

Figures (7)

  • Figure 1: Overview of the proposed method, which consists of constraint extraction and scheduling phases.
  • Figure 2: Examples of extracted constraints using template $T_1$.
  • Figure 3: Examples of excluded exceptional constraints.
  • Figure 4: Extracted constraints using template $T_3$: Available work days.
  • Figure 5: Extracted constraints using template $T_4$: Required staff for each shift for each day of the week.
  • ...and 2 more figures