Improved Transportation Systems Based on Evolved Business Intelligence

Intelligent transportation systems offer various services to all parties involved in transportation activities. Route planning is a common and challenging problem in transportation. Therefore, the quality of metaheuristic approaches to this problem is crucial, as it is now a planning module in almost all intelligent transportation systems available. On the other hand, improving the structure of intelligent transportation systems using business intelligence can address management challenges. The purpose of this paper is to analyze and apply business intelligence, specifically a combined genetic algorithm with a harmony search algorithm, to solve a transportation problem. The transportation problem is chosen as a challenging computational experiment in this research. To evaluate the behavior of the investigated methods, two examples of medium-sized intelligent transportation systems that cover large areas have been proposed. The research approach is based on a factor-based model. Agent-based modeling is used, which is an approach based on the idea that a system is composed of individual decentralized 'agents' that interact with each other according to local knowledge. The text also mentions special types of artificial agents that are created by simulating nature models.

کلیدواژه ها:

Intelligent Transportation Systems ، Business Intelligence ، Genetic Algorithm ، harmony search algorithm