Abstract. This paper focuses on the passenger traffic bottlenecks occurred in the bus route network in disaster situations and proposes the multi-agent based bus route optimization method to resolve such bottlenecks by generating the networks which can effectively transport many stranded persons including ones who wait around the station as the passenger traffic bottlenecks. For this purpose, the proposed method modifies the bus route networks generated as usual conditions to suitably pass many bus lines to and redistribute the buses among the bus lines according to the number of passengers. The intensive simulations have revealed the following implications: (1) the proposed bus route network optimization method generates the route network which is suitable for passenger traffic bottlenecks; (2) the proposed method decreases a risk of the bottlenecks; and (3) our method transports the passengers faster than those by the conventional one in various virtual disaster situations.
To optimise the flight schedule that consists of: 1) the regular flight operated on the same day and time through one year; 2) the non-regular flight operated on the different day and time according to month, this paper proposes the new multi-objective fleet assignment method that considers both the regular and non-regular flights. To investigate the effectiveness of our method, this paper applies it to Japanese domestic airport network optimisation for two months, on-and off-peak months, using a real-world data. The intensive simulation have revealed that the following implications: 1) our method can evolve a flight network that can be applied into the on-and off-peak month; 2) our method can find a flight network that has a well-balanced profit between on-and off-peak months; 3) in peak month, our method can find a flight network that has higher profit.
To optimize the problem composed of (i) the common components which should be optimized from the viewpoint of all objective functions and (ii) the special components which should be optimized from the viewpoint of one of the objective functions, this paper proposes a new multi-objective optimization method which optimizes not only the common components for all objective functions but also the special ones for each objective function. To investigate the effectiveness of the proposed method, this paper tested our method on the test-bed problem which is an extended version of the 0/1 knapsack problem. The intensive experiments have revealed the following implications: (i) Our method finds better solutions which have higher fitness than the conventional method (NSGA-II); (ii) our method can find the solutions that had a large norm (which corresponds to a high profit of an airline company in the flight scheduling problem) with the high rate of the common components; and (iii) since the crowding distance employed in our method contributes to keeping the diversity during the solution search, our method has high exploration capability of solutions.
This paper focuses on the passenger traffic bottlenecks occurring in the bus route network in disaster situations and proposes the multi-agent-based bus route network optimisation method to resolve such bottlenecks by generating the networks which can effectively transport many stranded persons who wait around the station as the bottlenecks. For this purpose, the proposed method modifies the bus route networks generated as usual situations to suitably generate the bus lines and redistribute the buses among the lines according to the number of passengers. The intensive simulations have revealed the following implications: the proposed method 1) can optimise the bus route network which is suitable for the bottlenecks; 2) optimises the bus route network which can cope with the hard disaster situations without an additional buses; 3) has the capability of decreasing a risk of the bottlenecks by concentrating on a modification of the lines having the bottleneck stations.Keywords: route optimisation; multi-agent system; traffic bottleneck; disaster; stranded persons.Reference to this paper should be made as follows: Morimoto, S., Jinba, T., Kitagawa, H., Takadama, K., Majima, T., Watanabe, D. and Katuhara, M. (2016) 'Multi-agent-based bus route optimisation for restricting passenger traffic bottlenecks in disaster situations', Int.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.