Table · dataset · 2026
A multi-objective constraint programming–satisfiability model for non-unit repetitive construction scheduling
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<p>Non-unit repetitive construction projects, in which activity groups are repeatedly executed over work-group-specific units rather than over a common set of identical production units, are difficult to schedule because activity sequences, crew movements, and execution logic vary across crew options.
Description
This study develops a multi-objective Constraint Programming–Satisfiability (CP-SAT) model for non-unit repetitive construction scheduling.
The model integrates crew–option selection, interval-based scheduling, route-based crew logic, transfer-dependent travel times, optional interruption, and sequence control within a unified framework. Both soft and hard sequencing requirements are represented: soft sequences emerge from optimized crew routes, while hard sequences can enforce prescribed order, same-crew execution, and immediate-successor relationships when required.
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An exact ε-constraint procedure is used for the bi-objective time-cost case, while sampled frontier generation supports higher-dimensional trade-off analysis. From a practical perspective, the framework helps project managers compare feasible scheduling alternatives and balance competing priorities related to project deadlines, budget, construction quality, and crew continuity. The proposed model therefore provides a rigorous and practical decision-support framework for complex non-unit repetitive construction projects.</p> <p></p><p>CP-SAT model for non-unit repetitive scheduling.</p><p>Soft and hard sequencing are modeled explicitly.</p><p>Crew routes, travel, and interruption are jointly captured.</p><p>Duration, cost, quality, and interruption are optimized.</p><p>Exact and sampled Pareto strategies are distinguished.</p><p></p> <p>CP-SAT model for non-unit repetitive scheduling.</p> <p>Soft and hard sequencing are modeled explicitly.</p> <p>Crew routes, travel, and interruption are jointly captured.</p> <p>Duration, cost, quality, and interruption are optimized.</p> <p>Exact and sampled Pareto strategies are distinguished.</p>
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Where it is published
- DOI doi.org/10.6084/m9.figshare.33660195.v1 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
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- Sequencing 75%
Provenance · 1 source records, 20 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| figshare | oai:figshare.com:article/33660195 | 9 d ago | JSON v1 |
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|---|---|---|---|
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| concepts[field].anzsrc:field:440710 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Science Policy'] |
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| concepts[field].local:field:chemistry | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| concepts[field].local:field:life-sciences | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| concepts[modality].local:modality:sequencing | enrichment · figshare com | keyword-concept-rules@1.0.0 | title+description (75%) |
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| license | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/rights |
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