A Quantum Annealing Algorithm for the Resource-Constrained Excavator Procurement Problem

This paper investigates a constrained excavator procurement problem (RCEPP), in which the budget is restricted and the performance of the excavators in collaboration with the pre-purchased mining trucks is considered. The RCEPP consists of deciding the purchase quantity of excavators to maximize the profit from the mining system composed of the imported excavators and the existing mining trucks. A mixed integer programming model (MIP) is established to address the RCEPP. In line with the specifications of quantum computers, a quadratic unconstrained binary optimization model is developed via reformulating the MIP. The scheduling scheme is coded into the ground state of the Hamiltonian operator, and the problem is solved using an optical coherent Ising machine (CIM). The experimental results indicate that, compared to traditional computation methods, quantum computers are capable of achieving better global optimal solutions. It has great application potential.