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The transportation routing problem is a very popular field in operations research and management science area. Many previous studies are still continuing to develop models and algorithms to produce the best transportation route optimization in various research objects. Technology has enabled the development of the intelligent decision support system (DSS) to optimize transportation route. Although technology has evolved, there are still few studies that build DSS software to minimize transportation distance and fuel consumption, especially using the metaheuristic approach. Thus, this paper aims to develop an intelligent DSS software to minimize fuel consumption and travel distance by considering time windows constraint using metaheuristic approach. The software can receive input dynamically to evaluate and select the best transportation route. The results of this software have been tested using real system data from one of tour and travel company in Indonesia. The company provides travel services using a bus to visit several tourist attractions based on the opening hours of the destinations. Intelligent DSS software output shows that the travel distance is 25.64% more efficient than the current real conditions. In addition, the fuel consumption produced by DSS is better than the actual conditions, which is 17.35% more efficient.