This paper proposes a multiagent-based route optimization method as a next-generation transportation system to generate a sustainable route network which can transport stranded persons effectively even if the road conditions are changed in a disaster situation. For this purpose, we apply a multiagent approach into the route optimization method where an agent corresponds to one route. Such an approach is very useful in a disaster situation because it is easy to add/delete routes and modify their routes according to the dynamic condition change and constraints. Towards a sustainable route network by multiagent approach, our route optimization method (1) employs the bus stop clustering method to generate clustered routes, (2) introduces a cluster-extension method to connect routes in different clusters and (3) adopts the evaluation function in consideration of damage by a change in the condition of roads. Intensive simulations on Mandl's urban transport benchmark problem have revealed the following implications: (1) the proposed method has succeeded in reducing stranded persons, detour persons, detour time, all of which are caused by road condition changes; (2) detour routes have emerged, which contribute to an increasing network sustainability; and (3) we have succeeded in reducing both the passenger's transportation time and the number of buses in a non-damaged situation.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.22(2014) No.2 (online)DOI http://dx.doi.org/10.2197/ipsjjip.22.235------------------------------This paper proposes a multiagent-based route optimization method as a next-generation transportation system to generate a sustainable route network which can transport stranded persons effectively even if the road conditions are changed in a disaster situation. For this purpose, we apply a multiagent approach into the route optimization method where an agent corresponds to one route. Such an approach is very useful in a disaster situation because it is easy to add/delete routes and modify their routes according to the dynamic condition change and constraints. Towards a sustainable route network by multiagent approach, our route optimization method (1) employs the bus stop clustering method to generate clustered routes, (2) introduces a cluster-extension method to connect routes in different clusters and (3) adopts the evaluation function in consideration of damage by a change in the condition of roads. Intensive simulations on Mandl's urban transport benchmark problem have revealed the following implications: (1) the proposed method has succeeded in reducing stranded persons, detour persons, detour time, all of which are caused by road condition changes; (2) detour routes have emerged, which contribute to an increasing network sustainability; and (3) we have succeeded in reducing both the passenger's transportation time and the number of buses in a non-damaged situation.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.22(2014) No.2 (online)DOI http://dx.doi.org/10.2197/ipsjjip.22.235------------------------------