Route Discovery Development for Multiple Destination Using Artificial Ant Colony

Google MAP Case Study

Keywords: Multiple destination route discovery, Google Map application, the shortest path, ant colony optimization algorithm


Smart cities need a smart applications for the citizen, not just digital devices. Smart applications will provide a decision-making to users by using artificial intelligence. Many real-world services for online shopping and delivery systems were used and attracted customers, especially after the Covid-19 pandemics when people prefer to keep social distance and minimize social places visiting. These services need to discover the shortest path for the delivery driver to visit multiple destinations and serve the customers. The aim of this research is to develop the route discovery for multiple-destination by using ACO Algorithm for Multiple destination route planning. ACO Algorithm for Multiple destination route planning develops the Google MAP application to optimize the route when it is used for multiple destinations and when the route is updated with a new destination. The results show improvement in the multiple destination route discovery when the shortest path and the sequence order of cities are found. In conclusion, the ACO Algorithm for Multiple destination route planning simulation results could be used with the Google Map application and provide an artificial decision for the citizen of Erbil city.  Finally, we discuss our vision for future development.


Download data is not yet available.

Author Biographies

Reem J. Ismail, Department of Computer Science, Cihan University-Erbil, Kurdistan Region, Iraq

Reem Jafar Ismail is an Assistant Professor at the Department of Computer Science, Faculty/College of Science, Cihan University-Erbil. She got the B.Sc. degree in computer science, the M.Sc. degree in computer science and the Ph.D. degree in computer science- wireless networks. Her research interests are in wireless networks, E-learning, and visual programming. Dr. Reem is a professional member of IEEE.

Mohammed H. Shukur, Department of Computer Science, Chian University-Erbil, Kurdistan Region, Iraq

Mohammed Hussein Shukur, faculty member At the department of Computer Science, college of science, Cihan University-Erbil. He holds a B.Sc. in computer science, a PgDip in data security, and an M. Tech. in computer science. His research interests in Big Data and Bioinformatics.

Samar J. Ismael, Department of Electromechanical Engineering, University of Technology, Baghdad, Iraq

Samar Jaafar Ismael is a lecturer at the Department of Electromechanical Engineering, Faculty/ College of Engineering, University of Technology/ Baghdad. She got the B.Sc. degree in electrical engineering, the M.Sc. degree in electrical engineering and the Ph.D. degree in electrical engineering – power system. Her research interests are in power system analysis and planning, artificial intelligent and technology education. Dr. Samar is a member of postgraduate studies and advisor of e-learning and website of the department. She is a reviewer in SCEE2018, CIC-COCOS’19 and ICEMEA’22 conferences.


S. Aslam and H. S. Ullah. A comprehensive review of smart cities components, applications, and technologies based on internet of things. ArXiv, vol. 2002, p. 01716, 2020.

A. Kousis and C. Tjortjis. Data mining algorithms for smart cities: A bibliometric analysis. Algorithms, vol. 14, p. 242, 2021.

A. T. Kareem, M. A. Alrawi and T. A. Israa. smart inventory control system based on wireless sensor network. International Journal of Engineering Research and Application, vol. 7, no. 8, pp. 40-47, 2017.

J. Zhang, J. Fan and Z. Luo. Generating multi-destination maps. IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 8, pp. 1964-1976, 2017.

H. Siam and M. B. Younes. Multi-destinations Round Trip Planner Protocol. 2018 5th International Symposium on Innovation in Information and Communication Technology (ISIICT), pp. 1-5, 2018.

A. Behrouz. Data Communications and Networking. 5th ed. McGraw-Hill, New York, pp. 601-602, 2013.

A. F. Alkhazraji, S. J. Ismail and Y. N. Abd. Iraqi national grid restoration strategy based on modified depth first search algorithm. Advances in Natural and Applied Sciences, vol. 10, no. 5. pp. 1-12, 2016.

A. F. Alkhazraji and S. J. Ismail. Restoring the Iraqi transmission network using k-shortest path algorithms. Advances in Natural and Applied Sciences, vol. 11, no. 4, pp. 146-158, 2017.

H. F. Hasan, A. A. Mahdi and M. Nat. A Recommendation of Information System Implementation to Support Decision-making Process of Top Management. In: Proceedings of the International Conference on Bioinformatics and Computational Intelligence, 2017.

C. Yang and K. Y. Szeto. Solving the Traveling Salesman Problem with a Multi-Agent System. 2019 IEEE Congress on Evolutionary Computation (CEC), 2019, pp. 158-165.

Y. Huang, J. C. Ying, P. S. Yu and V. Tseng. Dynamic graph mining for multi-weight multi-destination route planning with deadlines constraints. ACM Transactions on Knowledge Discovery from Data, vol. 15, no. 1, pp. 1- 2, 2021.

S. Kumar, V. Kumar-Solanki, S. K. Choudhary, A. Selamat and R. González-Crespo. Comparative study on ant colony optimization (ACO) and K-means clustering approaches for jobs scheduling and energy optimization model in internet of things (IoT). International Journal of Interactive Multimedia and Artificial Intelligence, vol. 6, no. 1, 2020.

H. Zhuang, K. Dong, Y. Qi, N. Wang and L. Dong. Multi-destination path planning method research of mobile robots based on goal of passing through the fewest obstacles. Applied Science, vol. 11, p. 7378, 2021.

M. Asaduzzaman, T. K. Geok, F. Hossain, S. Sayeed, A. Abdaziz, H. Y. Wong, C. P. Tso, S. Ahmed and B. A. Bari. An efficient shortest path algorithm: multi-destinations in an indoor environment. Symmetry, vol. 13, p. 421, 2021.

A. Hakeem, N. Gehani, X. Ding, R. Curtmola and C. Borcea. Multi-Destination Vehicular Route Planning with Parking and Traffic Constraints. In: MobiQuitous 19: Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. pp. 298-307, 2019.

E. H. C. Lu, W. Lee and V. Tseng. Mining fastest path from trajectories with multiple destinations in road networks. Knowledge and Information Systems, vol. 29, no. 1. pp. 25-53. 2011.

Available from: [Last accessed on 2022 Feb 01].

A. M. Luthfi, N. Karna and R. Mayasari. Google Maps API Implementation on IOT Platform for Tracking an Object Using GPS. In: 2019 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob). 2019.

Available from: [Last accessed on 2022 Feb 01].

How to Cite
Ismail R, Shukur M, Ismael S. Route Discovery Development for Multiple Destination Using Artificial Ant Colony. cuesj [Internet]. 20Aug.2022 [cited 2Dec.2023];6(2):41-8. Available from:
Research Article