Quantum Route Optimization With Delivery Time and Workload Constraints

The patent transforms the vehicle routing problem into an Ising model by changing the parameter representation from classical routing variables to quantum spin variables. This parameter transformation enables the problem to be solved using quantum computing while incorporating multiple constraints (delivery time windows, vehicle capacity, workload balancing) through carefully designed Hamiltonian terms, thus achieving both computational efficiency and solution realism.

The patent introduces an intermediary classical control system that bridges the quantum computer and the vehicle routing problem. This control system prepares the cost function with appropriate constraint terms, interprets the quantum computing results, and translates them back into realistic delivery plans. The intermediary ensures that quantum computational efficiency is maintained while delivering practically viable routing solutions.

The patent segments the complex constrained optimization problem into multiple independent constraint terms within the Hamiltonian function. Each constraint (delivery time windows, vehicle capacity, workload balancing) is represented as a separate term that can be independently formulated and tuned. This segmentation allows the system to manage complexity by addressing each constraint individually while maintaining the overall optimization framework.

The Ising model Hamiltonian serves as a universal framework that can accommodate multiple different types of constraints through a standardized mathematical form. The same quantum computing apparatus and optimization algorithm can handle various constraint types by simply modifying the Hamiltonian terms, providing multi-functionality without requiring separate systems for each constraint type.