Intelligent Optimization Scheduling Algorithm for Professional Sports Games

The world financial crisis has caused a great impact to human beings´ daily life. The significant evidence is that the oil price has hit, more than, 90 U.S. according to the report of ministry of economic affairs. The price reflects the difficulty not only to transportation but finance status. In this paper, an optimization algorithm concerning the scheduling issues was proposed. The algorithm was revised in accordance with Tabu Search algorithm and Genetics algorithm. The purpose of this work is to reduce the travelling cost, simply achieve the least expenditures. The information of famous sports league (e.g. NBA) was adopted as preliminary experiment data. The travelling distances, according to the matchups of 2009 NBA games, were collected and obtained the straight-line distances from Google Map API. As a result, our method could reduce, at least, around 14,000 kilometers under 45,000 times mutation with the rate at 0.1%.