Solving the travelling problem of thai tourism by improved ant colony optimization


Ms.ปุณยภัสร์ ชวรัตน์ธนรังษี, ผศ.ดร.สุเทพ ทองงาม


International journal of innovation, creativity and change


Most industries focus on how to profit from processing and transmitting, even in tourism. Technology has met travellers’ need to access information on problems regarding matters such as flights, routes, hotels, and transportation, by themselves. Computer science can help solve such problems, through Artificial Intelligence and animal simulations. This research applies Ant Colony Optimization to travelling problems. Brute Force computing was juxtaposed against the Ant Colony System. Some routes obtained from that System match the Brutes Force’s shortest distance, but some do not. Generating all possible Brute Force paths takes more time than Ant Colony System “algorithms”. The efficiency of the Brute Force algorithm is termed “Big O2” while the Ant Colony System is only “Big O”. Other conditions were added to that System, such as by changing vehicles at each tourist attraction, adding break points such as gas stations or restaurants, to complete planning. The Ant Colony System can be further expanded into one of tourist advice for tourist attractions’ recommended plans.

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