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Related Experiment Video

Updated: May 22, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
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Efficient scheduling of multiple software projects for work continuity and identical completion time.

Abdulrahman Aldhubaiban1, Ali AlMatouq1

  • 1Department of Engineering Management, Prince Sultan University, Riyadh, PO box 66863 Rafha Street, Riyadh, 11586, Riyadh, Saudi Arabia.

Methodsx
|March 17, 2025
PubMed
Summary
This summary is machine-generated.

This study presents a new model for optimizing software project scheduling. It ensures all projects finish simultaneously, minimizes costs, and maximizes resource utilization for efficient project management.

Keywords:
Automatic software managementEfficient Scheduling of Multiple Software Projects for Work Continuity and Identical Completion TimeMathematical modelMulti-objective optimizationSoftware project scheduling

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Area of Science:

  • Operations Research
  • Software Engineering Management

Background:

  • Efficiently managing multiple software projects with shared resources is crucial for meeting operational and strategic objectives.
  • Minimizing project costs and employee idle time requires seamless resource reallocation.

Purpose of the Study:

  • To develop a continuous variable nonlinear model for optimal scheduling of multiple software projects.
  • To ensure identical completion dates for all projects while maintaining resource continuity.

Main Methods:

  • Development of a continuous variable nonlinear programming model.
  • Utilization of cloud-based architecture for online optimization solver integration.
  • Validation through a random generator for large-scale software project instances.

Main Results:

  • The model successfully schedules up to 40 software projects and 100 employees.
  • Optimal solutions were found in under 21 minutes using nonlinear programming algorithms.
  • Demonstrated efficient resource reallocation and work continuity.

Conclusions:

  • The proposed model provides an effective solution for large-scale, multi-project software scheduling.
  • Cloud-based optimization enables efficient and timely problem-solving.
  • The approach minimizes costs and maximizes resource utilization in software development.