Most of import and export cargoes are transported by sea. For instance, bulk cargoes like oil, grain, coal and iron mine are shipped by tramp vessels over 130,000DWT. They are usually carried by large quantities, and the operation costs of these vessels are very high. For this reason, one of the shipping company’s major issues is to find the best schedule for transportation. This thesis focuses on tramp shipping, especially on industrial carriers that have their own ships.
Such major bulk cargoes as oil and grain usually have a concentrated production confined on a specific geographic location. So they are transported from a few ports near the production location to many demand sites scattered all over the globe. This thesis concerns this transportation practices and has developed a decision making model for finding optimal ship schedules where there are a few loading ports.
The developed model is also an improvement over the existing model of Cho and Perakis which assumes only one loading port. By allowing it to have more than one loading ports, the model presented in this thesis reflects more instances of the real world tramp operation. Usual real world instances of the developed model can be solved to find the optimal ship schedules with commercial software for linear and integer programming.