A multi-inner-world Genetic Algorithm to optimize delivery problem with interactive-time

Building a delivery route optimization system that improves the delivery efficiency in real time requires to solve several tens to hundreds cities Traveling Salesman Problems (TSP) within interactive response time, with expert-level accuracy (less than 3% of errors). To meet these requirements, a multi-inner-world Genetic Algorithm (Miw-GA) method was developed. This method combines two types of GApsilas inner worlds such as a 2-opt type mutation world and an NI type mutation world, randomly selecting either one of these mutation methods (inner worlds) each generation in a GA world consisting of the whole generations. This method is compared with other related works based on experimental results.