﻿This readme file was generated on [2025-02-21] by [Yingpei Sun]



GENERAL INFORMATION

Title of Dataset: Processed Construction Task Data for Multi-Objective Optimization of Construction Scheduling Based on Grey Wolf Optimization Algorithm 


Author/Principal Investigator Information
Name: Yingpei Sun
ORCID: https://orcid.org/0009-0000-9258-299X
Institution: Durham university
Address: Lower Mountjoy, South Rd, Durham DH1 3LE
Email: yingpei.sun@durham.ac.uk

Author/Associate or Co-investigator Information
Name: Qing Wang
ORCID:https://orcid.org/0000-0002-7631-129X
Institution: Durham university
Address: Lower Mountjoy, South Rd, Durham DH1 3LE
Email: qing.wang@durham.ac.uk

Author/Alternate Contact Information
Name: David Toll
ORCID:https://orcid.org/0000-0002-9440-9960
Institution: Durham university
Address: Lower Mountjoy, South Rd, Durham DH1 3LE
Email: d.g.toll@durham.ac.uk

Author/Alternate Contact Information
Name: Stefan Szyniszewski
ORCID:https://orcid.org/0000-0002-7862-8506
Institution: Durham university
Address: Lower Mountjoy, South Rd, Durham DH1 3LE
Email: stefan.t.szyniszewski@durham.ac.uk

Date of data collection: 2024-10-25

Geographic location of data collection: Not applicable (data derived from published literature)

Information about funding sources that supported the collection of the data: None


SHARING/ACCESS INFORMATION

Licenses/restrictions placed on the data: This dataset is available under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). Users are free to share and adapt the data, provided that proper attribution is given.  

Links to publications that cite or use the data: None

Links to other publicly accessible locations of the data: This dataset is only available in the Durham University Research Data Repository.

Links/relationships to ancillary data sets: None

Was data derived from another source?
If yes, list source(s): 
Li, Y., Wu, J., Hao, Y., Gao, Y., Chai, R., Chai, S., & Zhang, B. (2024). Process scheduling for prefabricated construction based on multi-objective optimization algorithm. Automation in Construction, 168(A), 105809. https://doi.org/10.1016/j.autcon.2024.105809
Liu, H., Al-Hussein, M., & Lu, M. (2015). BIM-based integrated approach for detailed construction scheduling under resource constraints. Automation in Construction, 53, 29–43. https://doi.org/10.1016/j.autcon.2015.03.008

Recommended citation for this dataset: Sun, Y., Wang, Q., Toll, D., & Szyniszewski, S. Multi-objective optimization of construction scheduling based on Grey Wolf Optimization algorithm


DATA & FILE OVERVIEW

File List: 
Construction_Task_ProcessedData1.xlsx: Processed task scheduling data, including task IDs, required materials, and time estimates.
Construction_Task_ProcessedData2.xlsx: Processed task scheduling data, including task IDs, required materials, and time estimates.
README.txt: Documentation describing the dataset.

Relationship between files, if important: Not applicable

Additional related data collected that was not included in the current data package: Noe

Are there multiple versions of the dataset? No
If yes, name of file(s) that was updated: 
Why was the file updated? 
When was the file updated? 


METHODOLOGICAL INFORMATION

Description of methods used for collection/generation of data: 
The dataset was extracted from multiple research papers and reports related to construction scheduling. The original data sources include numerical values and task descriptions from academic literature, which were manually compiled into a structured format. 
Li, Y., Wu, J., Hao, Y., Gao, Y., Chai, R., Chai, S., & Zhang, B. (2024). Process scheduling for prefabricated construction based on multi-objective optimization algorithm. Automation in Construction, 168(A), 105809. https://doi.org/10.1016/j.autcon.2024.105809
Liu, H., Al-Hussein, M., & Lu, M. (2015). BIM-based integrated approach for detailed construction scheduling under resource constraints. Automation in Construction, 53, 29–43. https://doi.org/10.1016/j.autcon.2015.03.008 

Methods for processing the data: 
The raw data extracted from literature sources was manually cleaned and structured into an Excel dataset. The following steps were performed:  
1. Standardized column names for consistency.  
2. Converted all time-related variables to hours (h) for uniformity.  
3. Replaced "/" in the `Predecessor_Tasks` column with "NULL" to indicate missing values.  
4. Changed multiple predecessor task IDs from comma-separated to semicolon-separated to avoid CSV parsing issues.  
5. Removed duplicate records and ensured each `Task_ID` was unique.  

Instrument- or software-specific information needed to interpret the data: 
The dataset is provided in Excel (.xlsx) format and can be opened with Microsoft Excel or equivalent spreadsheet software. 

Standards and calibration information, if appropriate: Not applicable.

Environmental/experimental conditions: Not applicable.

Describe any quality-assurance procedures performed on the data: 
Manual verification of extracted values from source literature.  
Cross-checking numerical consistency between sources.  
Removal of incomplete or duplicate task records.  
Standardization of time units and task dependencies.  

People involved with sample collection, processing, analysis and/or submission: Yingpei Sun (Durham University)


DATA-SPECIFIC INFORMATION FOR: 
Construction_Task_ProcessedData1.xlsx.

Number of variables: 3

Number of cases/rows: 5

Variable List: 
Variable Name	Description	Unit
Task_ID	Unique identifier for each task	-
Task_Name	Name of the construction task	-
Predecessor	ID of the task that must be completed before this task can start (NULL if no predecessor)	-

Missing data codes: NULL

Specialized formats or other abbreviations used: 
NONE

Number of variables: 5

Number of cases/rows: 8

Variable List: 
Variable Name	Description	Unit
Task_ID	Unique identifier for each task	-
Component	The structural component involved in the task	-
Activity	Description of the specific activity performed	-
Required_Resources	List of crews needed to perform the activity	-
Productivity	Work rate (varies based on unit)	See Unit

Missing data codes: NULL

Specialized formats or other abbreviations used: 
- Productivity is given in different units based on task type:
  - Panels per minute (`panel/T(time)).
  - Connections per minute (`connections/min).
  - Square feet per day (`s.f./day).
  - Cubic meters per day (`m³/day).
  - Tons per day (`ton/day).

Number of variables: 2

Number of cases/rows: 8

Variable List: 
Variable Name	Description	Unit
Resource	Name of the labor or equipment required	-
Quantity	Number of crews available for the task	Count

Missing data codes: NULL

Specialized formats or other abbreviations used: None

DATA-SPECIFIC INFORMATION FOR: 
Construction_Task_ProcessedData1.xlsx.

Number of variables: 7

Number of cases/rows: 10

Variable List: 
Variable Name	Description	Unit
Task_ID	Unique identifier for each task	-
Demand_Area	Construction area where task is required	-
Required_Material	Material type required for task	-
Required_Quantity	Quantity of material required	Units
Task_Time_h	Estimated time to complete task	Hours
Unit_Loading_Time_h	Time required to load one unit of material	Hours
Unit_Unloading_Time_h	Time required to unload one unit of material	Hours

Missing data codes: NULL

Specialized formats or other abbreviations used: 
NONE

Number of variables: 2

Number of cases/rows: 10

Variable List: 
Variable Name	Description	Unit
Task_ID	Unique task identifier	-
Predecessor_Tasks	IDs of predecessor tasks	-

Missing data codes: NULL

Specialized formats or other abbreviations used: 
`Predecessor_Tasks` uses semicolons (`;`) to separate multiple task IDs.  

Number of variables: 3

Number of cases/rows: 7

Variable List: 
Variable Name	Description	Unit
Material_ID	Unique identifier for each material	-
Material_Name	Name of the construction material	-
Loading_Time_h_per_piece	Time required to load one unit of material	Hours
Unloading_Time_h_per_piece	Time required to unload one unit of material	Hours

Missing data codes: NULL

Specialized formats or other abbreviations used: 
None

Number of variables: 6

Number of cases/rows: 38

Variable List: 
Variable Name	Description	Unit
Task_ID	Unique identifier for each task	-
Process_Name	Name of the process or activity	-
Process_Time_h	Estimated time to complete the process	Hours
Area	Location or construction zone	-
Material	Material used in the process	-
Quantity	Quantity of material required	Units

Missing data codes: NULL

Specialized formats or other abbreviations used: 
None

Number of variables: 2

Number of cases/rows: 74

Variable List: 
Variable Name	Description	Unit
Task_ID	Unique task identifier	-
Predecessor_Tasks	IDs of predecessor tasks	-

Missing data codes: NULL

Specialized formats or other abbreviations used: 
`Predecessor_Tasks` uses semicolons (`;`) to separate multiple task IDs.  