Abstract
In recent years, on-demand transport systems (such as a demand-bus system) are focused as a new transport service in Japan. An on-demand vehicle visits pick-up and delivery points by door-to-door according to the occurrences of requests. This service can be regarded as a cooperative (or competitive) profit problem among transport vehicles. Thus, a decision-making for the problem is an important factor for the profits of vehicles (i.e., drivers). However, it is difficult to find an optimal solution of the problem, because there are some uncertain risks, e.g., the occurrence probability of requests and the selfishness of other rival vehicles. Therefore, this paper proposes a transport policy for on-demand vehicles to control the uncertain risks. First, we classify the profit of vehicles as “assured profit” and “potential profit”. Second, we propose a “profit policy” and “selection policy” based on the classification of the profits. Moreover, the selection policy can be classified into “greed”, “mixed”, “competitive”, and “cooperative”. These selection policies are represented by selection probabilities of the next visit points to cooperate or compete with other vehicles. Finally, we report simulation results and analyze the effectiveness of our proposal policies.
Similar content being viewed by others
References
Ohta M, Shinoda K, Noda I, Kurumatani K, Nakashima H (2002) Usability of demand-bus in town area. Technical Report 2002-ITS-11-33, Technical Report of IPSJ (in Japanese)
Noda I, Ohta M, Shinoda K, Kumada Y, Nakashima H (2003) Is demand bus reasonable in large scale towns? Technical Report 2003-ICS-131, Technical Report of IPSJ (in Japanese)
Harano T, Ishikawa T (2004) On the validity of cooperated demand bus. Technical Report 2004-ITS-19-18, Technical Report of IPSJ (in Japanese)
Desrochers M, Lenstra J, Savelsbergh M, Soumis F (1988) Vehicle routing with time windows: optimization and approximation. In: Vehicle routing: methods and studies, pp 65–84
Solomon M, Desrosiers J (1988) Time window constrained routing and scheduling problems. Transp Sci 22:1–13
Thangiah S (1995) Vehicle routing with time windows using genetic algorithms. In: Chambers L (ed) Application handbook of genetic algorithms: new frontiers, vol II. CRC Press, Boca Raton, pp 253–277.
Potvin JY, Bengio S (1996) The vehicle routing problem with time windows, part II: genetic search. INFORMS J Comput 8:165–172
Louis SJ, Yin X, Yuan ZY (1999) Multiple vehicle routing with time windows using genetic algorithms. In: Angeline PJ, Michalewicz Z, Schoenauer M, Yao X, Zalzala A (eds) Proceedings of the congress on evolutionary computation, vol 3, Mayflower Hotel, Washington, DC, USA. IEEE Press, New York, pp 1804–1808
Gambardella LM, Taillard É, Agazzi G (1999) MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows. In: Corne D, Dorigo M, Glover F (eds) New ideas in optimization. McGraw-Hill, New York, pp 63–76
Montemanni R, Gambardella L, Rizzoli A, Donati A (2003) A new algorithm for a dynamic vehicle routing problem based on ant colony system. In: Proceedings of ODYSSEUS 2003: second international workshop on freight transportation and logistics, Palermo, Italy, pp 27–30
Koutsoupias E, Papadimitriou CH (1999) Worst-case equilibria. In: Proceedings of the 16th annual symposium on theoretical aspects of computer science, pp 387–396
Roughgarden T, Tardos E (2000) How bad is selfish routing? In: IEEE symposium on foundations of computer science, pp 93–102
Roughgarden T (2002) The price of anarchy is independent of the network topology. In: Proceedings of the 34th ACM symposium on the theory of computing, pp 428–437
Mukai N, Feng J, Watanabe T (2005) Dynamic construction of routine patterns for transport vehicles based on ant colony system. J Inf Process Soc Jpn 46:2687–2694
Mukai N, Feng J, Watanabe T (2005) Proactive route planning based on expected rewards for transport systems. In: Proceedings of IEEE international conference on tools with artificial intelligence, pp 51–57
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mukai, N., Watanabe, T. Simulation analysis of decision-making policy for on-demand transport systems. Appl Intell 31, 225–233 (2009). https://doi.org/10.1007/s10489-008-0125-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10489-008-0125-z