Quantum-Inspired Intelligent Traffic Route Optimization in Transportation Systems Using Metaheuristic Optimization
Egreen Quanta
- Organisation
- Egreen Quanta
- Department
- Egreen Quanta
- Category
- Software
- Theme
- Transportation & Logistics
- Submission deadline
- 5 October 20262026-10-05
- Ideas submitted
- 210/500
- Serial number
- 137
- Data captured on
- 2026-10-02
- Dataset link
- Public/Open Additional Information regarding PS
- https://drive.google.com/file/d/1iubIiKS9NPr2lpYMVTt2MxgC_qRq5NnM/view?usp=drive_link(opens drive.google.com in a new tab)
- Contact info
- No contact published
- Youtube link
- No video published
Background Modern urban transportation networks face persistent challenges of traffic congestion, inefficient route planning, and high operational costs. Classical optimization techniques struggle with large-scale Vehicle Routing Problems (VRP) because of their NP-hard nature. While quantum computers offer theoretical advantages for combinatorial optimization,current hardware limitations prevent their direct large-scale use. Quantum-inspired metaheuristic algorithms (e.g., Quantum Particle Swarm Optimization - QPSO) embed quantum-mechanical concepts into classical computation, delivering stronger global search, faster convergence, and a better balance between exploration and exploitation. Problem Description Develop a quantum-inspired metaheuristic optimization framework that dynamically generates near-optimal vehicle routes under real-time or simulated traffic conditions.The transportation network will be modelled as a weighted graph. The framework will focus on algorithms such as Quantum Particle Swarm Optimization (QPSO) and will be benchmarked against conventional metaheuristics and exact methods. Objectives 1. Design a quantum-inspired metaheuristic framework capable of solving large-scale VRP and shortest-path problems.
- Minimize total travel time, distance, and traffic congestion.
- Reduce computational complexity while improving convergence speed and solution quality compared with classical algorithms.
- Demonstrate scalability for smart-city logistics and intelligent transportation systems.
Expected Solution A complete software platform that implements a Quantum-Inspired Metaheuristic Optimization Algorithm for intelligent traffic routing. The platform must include graph-based network modelling, mathematical formulation of the optimization problem,constraint handling, convergence analysis, and systematic performance benchmarking. Add 'Delivery Table (Expected Deliverables)' here