Quantum Inspired Binary Atom Search Optimization Algorithm for Charging Station Placement Problem

Charging station location and capacity optimization is a critical issue in the field of electric vehicle (EV) infrastructure planning as it involves multiple objectives and constraints. In this case, finding optimal solution for charging station placement problem requires an efficient optimization tool that could find quality solutions in short time. With this in mind, this work proposes a novel binary variant of atom search optimization (ASO) algorithm, utilizing the concept of quantum binarization technique, namely quantum-inspired binary ASO (QBASO) algorithm. The proposed QBASO possesses the same structure as original ASO algorithm, but the binarization procedure is performed using quantum gates and quantum bits. The performance of the proposed QBASO is tested using well-known benchmark functions and is then applied on EV charging station placement problem. The experimental results and statistical analyses show that QBASO algorithm is a promising optimization technique for solving charging station placement problem.