A multi-inner-world Genetic Algorithm using multiple heuristics to optimize delivery schedule

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 is developed. This method combines several types of GA´s inner worlds. Each world of this method uses a different type of heuristics such as a 2-opt type mutation world and a block (nearest insertion) type mutation world. Comparison based on the results of 1000 times experiments proved the method is superior to others.