Review and comparison of hybridized ACO capabilities in locating warehouse benefits from KSA manufacturable raw materials

Multi-echelon supply chain problems involving sources, warehouses, and customers are categorized as NP-complete. This review highlights the hybridized Ant Colony Optimization (hACO) approach in meeting accurate coordinates of the Integrated Industrial Complex (IIC), which relies on manufacturable KSA raw material useful in many industries, such as feldspar, bauxite, phosphate, limestone, silica sand, copper, and its by-products (i.e., source). The review highlights that hACO mathematically improved the determination of an economic coordinate for an IIC (i.e., warehouse) when fed by raw material locations according to their reserves and customer destinations. The review relies on expert questionnaires and scientific papers published in SCOPUS, Google Scholar, and WOS via key search indicators (KSIs), which are location coordinates, reserve availability, and EPQ capability that represent the source. In contrast, the KSI for the IIC location (i.e., warehouse) focuses on the total logistics cost, expected domestic production, and exportability. The review has been conducted in two sections. The first section identifies the source locations and their EPQ. The second section draws the researchers’ attention to the capabilities of hACO algorithms in determining the economic location of an IIC (i.e., warehouse). The C# code has been tailored by the author’s team to check the effectiveness of hACOs due to their convergence to deduce accurate IIC coordinates via suggesting an innovative approach bi-hACO, which guarantees minimum transportation costs. The review reveals that ACO-ML, Mat-ACO-SGD, Mat-AGWO-ACO, Mat-MMAS-QAP, and Mat-CH-ALOAO, which improved mathematically, help locate the IIC in Al-Jawf, Al-Qassim , and Al-Kharj regions. Mat-bi-hACO meets KPIs by 14%, 7%, 6%, 3%, and 0.7%.