Artificial neural network based meta-heuristic for performance improvement in physical internet supply chain network

<p>Nowadays, reducing total costs while enhancing customer satisfaction is a major task for many supply chain systems. To deal with this issue, the physical internet (PI) paradigm can be represented as potential replacement current logistics system. This paper devoted cost reduction and lead time improvement in PI-SCN using hybrid framework based on an artificial neural network (ANN) improved slime mould algorithm (ISMA). address performance of proposed framework, real-case study Morocco considered. The new trainer ISMA’s has been investigated three approximation datasets from University California at Irvine (UCI) machine-learning repository regarding nine recent metaheuristics. experimental results highlight effectiveness ISMA according to other meta heuristics training feed-forward networks (FNNs) converge speed avoid local minima.</p>