A web application utilizing Particle Swarm Optimization (PSO) to optimize job shop scheduling and monitoring in the construction industry.
Particle Swarm Optimization (PSO) is a computational method inspired by the social behavior of birds flocking or fish schooling. It is used to find optimal solutions to complex problems by iteratively improving a candidate solution with regard to a given measure of quality. In the context of a job shop scheduler in the construction industry, PSO can be used to optimize the manpower allocation and scheduling of tasks to improve efficiency and reduce costs.
In the construction industry, job shop scheduling is essential for effective resource management, timely project completion, cost containment, and overall project success. Managing risks, satisfying customer expectations, and preserving a competitive advantage are vital aspects of this sector. This system applies Particle Swarm Optimization (PSO) to optimize job shop scheduling and monitoring, ensuring efficient and successful project management.
- View the list of projects, manpower, and equipment.
- Create a project based on the input of construction project data such as project title, location, required manpower, and project tasks.
- Select and categorize the scale of the project, whether it is small or medium scale.
- Add new manpower and enter the total number of workers for the said manpower.
- Add new equipment and enter the equipment's productivity equivalent.
- Edit project resources such as manpower and equipment.
- Input the availability of workers and equipment.
- View the anticipated time needed to finish the project.
- View the generated schedule and assigned manpower and equipment computed by the PSO algorithm.
- Generate reports for task tracking and resource management.
- Front-end Tools and Frameworks:
- JavaScript
- ReactJS
- HTML
- CSS
- Back-end Tools and Frameworks:
- Python
- Flask
- Database Management System:
- PostgreSQL