A production-oriented backend system built using Java and Spring Boot that intelligently assigns tasks to volunteers based on multiple dynamic factors such as skills, availability, and workload.
In real-world team environments, assigning tasks manually or using simple rules often leads to:
- Poor resource utilization
- Overloaded team members
- Inefficient task handling
This project solves that by introducing a multi-factor decision engine for optimal task allocation.
Each volunteer is evaluated based on:
- Skill Match
- Availability
- Current Workload
The system computes a score and selects the best candidate dynamically.
- Tasks are processed based on urgency and deadlines
- Implemented using a priority queue (heap-based structure)
- Handles cases where no perfect match exists
- Assigns best possible candidate based on fallback logic
- Prevents overload using configurable limits
Supports multiple allocation strategies:
- Best Score Strategy
- Least Loaded Strategy
- Hybrid Strategy
Key endpoints include:
POST /tasks→ Create a taskPOST /assign→ Assign task to best-fit volunteerGET /volunteers/best-fit→ Fetch optimal candidateGET /analytics→ View system insights
- Task completion stats
- Volunteer efficiency
- Load distribution
- Java
- Spring Boot
- Spring Data JPA
- MySQL / PostgreSQL
- Maven
- Redis caching for faster lookup
- Docker containerization
- Async processing using message queues
controller/ → API endpoints
service/ → Business logic
engine/ → Task allocation logic
repository/ → Database interactions
model/ → Entity classes
- Designing scalable backend systems
- Implementing decision-making algorithms
- Applying data structures (priority queue)
- Building clean REST APIs
- Structuring production-level applications
- Real-time dashboard with charts
- Role-based access control
- Integration with frontend UI
- Advanced optimization algorithms
ARVIND KOSTA