A multiagent approach to designing the transportation domain is presented. The modeling autonomous cooperating shipping companies system (Mars) is described, which models cooperative order scheduling within a society of shipping companies. We argue why distributed artificial intelligence (DAI) offers suitable tools to deal with the hard problems in this domain. We present three important instances for DAI techniques that proved useful in the transportation application: cooperation among the agents, task decomposition and task allocation,and decentralized planning. An extension of the contract net protocol for task decomposition and task allocation is presented; we show that it can be used to obtain good initial solutions for complex resource allocation problems. By introducing global information based upon auction protocols, this initial solution can be improved significantly. We demonstrate that the auction mechanism used for schedule optimization can also be used for implementing dynamic replanning. Experimental results are provided evaluating the performance of different scheduling strategies.