Question 1

What is Q-Raftar (کیو-رفتار)?

Accepted Answer

Q-Raftar is a production-grade civic tech and quantum optimization platform designed for Karachi's public transit network. Developed by SBF Consultancy as a Fee-Sabeel-Allah public initiative, it models municipal and paratransit networks, formulates bus line scheduling and fleet reallocation as a Quadratic Unconstrained Binary Optimization (QUBO) Hamiltonian problem, executes on IBM Quantum backends, and renders results on an interactive spatial HUD.

Question 2

How does quantum computing optimize bus routes in Karachi?

Accepted Answer

Transit network routing is an NP-hard combinatorial problem where finding optimal bus assignments across thousands of potential road corridors causes classical computing bottlenecks. Q-Raftar translates transit hub demands, fleet capacities, and road distances into a quantum Hamiltonian. This Hamiltonian is converted to Pauli-Z spin operators and solved via Quantum Approximate Optimization Algorithms (QAOA) or Quantum Annealing on IBM Quantum processors (or Qiskit Aer simulators), minimizing deadhead kilometers and passenger wait times.

Question 3

What are the major bus routes in Karachi covered by Q-Raftar?

Accepted Answer

Q-Raftar actively models major transit arteries including Peoples Bus Service (PBS) Route 1 (Model Colony to Tower via Shahrah-e-Faisal), PBS Route 2 (North Karachi to Indus Hospital via Rashid Minhas), PBS Route 3 (Nagan Chowrangi to Korangi), PBS Route 9 (Gulshan-e-Hadeed to Tower), PBS Route 10 (Numaish to Sea View), Green Line BRT (Surjani Town to Numaish Central Interchange), the Orangi Feeder Corridor, and the Malir Cantt Express.

Question 4

What is the transit demand-supply gap in Karachi?

Accepted Answer

Karachi's metropolitan population of 20+ million requires an estimated 15,000 standard transit buses. Currently, fewer than 1,100 active mass transit buses operate, leading to severe seat capacity deficits. For instance, PBS Route 2 experiences a daily passenger demand of 38,500 commuters against a supply of only 19,200 seats (a 2.01 overload ratio). Q-Raftar's mathematical engine dynamically reallocates under-utilized vehicles to heavily overcrowded corridors.

Question 5

How much OPEX and fuel savings can Karachi achieve using Q-Raftar?

Accepted Answer

By eliminating up to 38.4% of empty deadhead kilometers between bus depots and optimizing inter-line headways, Q-Raftar projects a monthly reduction of over 149,000 liters of diesel fuel across the 8 surveyed corridors. At current diesel prices (~PKR 285/L), this translates to approximately PKR 42.6 Million in direct monthly operational savings while abating 396 metric tons of CO2 emissions.

Question 6

What is the SBF Consultancy CSR (Fee-Sabeel-Allah) disclosure?

Accepted Answer

Q-Raftar is offered 100% free of charge as an open public-service civic technology project under SBF Consultancy's Corporate Social Responsibility (CSR) Fee-Sabeel-Allah charter. All optimization models, datasets, and spatial dashboards are freely accessible to municipal authorities, transit operators, urban researchers, and citizens of Pakistan.

Question 7

How does Q-Raftar help prevent bus bunching and reduce passenger wait times?

Accepted Answer

Bus bunching occurs when uneven passenger boarding creates headways collapse. Q-Raftar models terminal dwell times, road congestion indices, and cycle times along OpenStreetMap topologies to calibrate dynamic dispatch headways (reducing average wait times from 21.4 minutes down to 8.2 minutes during peak hours).

Q-Raftar Karachi Quantum Transit Optimizer & Spatial Intelligence Platform

Key Karachi Bus Routes and Transit Corridors

Quantum QUBO and Hamiltonian Optimization

500+ High-Frequency Search Terms & Open Data Endpoints