A Multi-Objective Optimization for Supply Chain Management using Artificial Intelligence (AI)

Faculty Computer Science Year: 2022
Type of Publication: ZU Hosted Pages:
Authors:
Ibrahiem Mahmoud Mohamed Elhenawy
Journal: International Journal of Advanced Computer Science and Applications Science and Information (SAI) Organization Limited Volume: Volume 13
Keywords : , Multi-Objective Optimization , Supply Chain Management using    
Abstract:
Supply chain management seeks to solve the complex problems of transporting goods from the suppliers to the end customers. Improving the differentiation between different paths to reduce costs and time may require smart systems. This paper proposes two new algorithms for determining, with Multi-Objective Optimization, the least cost and the most appropriate path between two nodes. First: Ant colony optimization (ACO) algorithm, working alongside with Multi Objective Optimization (MOO), is adopted to determine the shortest path and time between two nodes to reach with the least cost. Multi-Objective intelligent Ant Colony (MOIAC) algorithm improves supply chain management to achieve the optimal and the most appropriate solutions. Second: Particle Swarm Optimization (PSO) algorithm, also working alongside MOO, is adopted to determine the least cost, time, and shortest path. Multi Optimization …
    
     
 
       

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