A Hybrid Quantum Inspired - Red Fox Optimization Algorithm For Container Storage Space Allocation Problem

Abstract

This study addresses the Storage Allocation Problem (SAP) in container terminal yards, focusing on discovering innovative strategies. The research introduces and evaluates the Quantum-inspired Particle Swarm Optimization (QPSO), Red Fox Optimization (RFO), and a novel Hybrid Quantum-inspired Red Fox Optimization (QI-RFO) algorithm. Applied to the Tan Cang - Cai Mep Thi Vai Terminal (TCTT), these metaheuristics are compared against traditional methods such as Mixed Integer Quadratic Programming (MIQP) and Improved Particle Swarm Optimization (IPSO). Results indicate that the metaheuristics of QPSO, RFO, and especially, Hybrid QI-RFO outperforms the benchmark methods, particularly in large-scale scenarios, demonstrating its robustness and potential applicability in real-world operations.