Learning routes within an intelligent on demand transport service

We propose in this article a case-based reasoning algorithm for enhancing intelligent transport systems. To deal effectively with a current real situation, the human brain tends to resort to similar situations encountered previously. Case Based Reasoning mimics human reasoning by storing historical cases in a case base, such as a human memory, for reuse when facing similar cases. In this work, the knowledge and experience gained in the past using optimization algorithms is used to search for solutions of a real on-demand transport problem. The proposed case based reasoning algorithm helps make the right decisions at the right time.