Novel Optimization Models for Complex Planning Problems in Maritime Transportation

Abstract

The purpose of this PhD thesis is to develop novel optimization models and formulations for three important planning problems in maritime transportation. Application of the operations research methods in the thesis can support the decision-making process faced by the shipping companies and ultimately lead to savings in costs and emissions.

The first two papers provide Roll-on Roll-off (RoRo) shipping companies with models for two versions of a combined fleet deployment and inventory management problem. The findings indicate that substantial cost reductions can be achieved by integrating fleet deployment and inventory management decisions, especially if one introduce the flexibility of not visiting all ports along a trade every time the trade is serviced. The model proposed in the third paper is used for analyzing the possibility for a model shift from trucks to maritime RoRo transportation in the distribution of cars in India. The trade-offs between emissions and costs are discussed, and it is shown that such a modal shift is economically viable and that it will have significant positive effects on the environment. Finally, the fourth paper considers a problem that combines traditional fleet deployment with speed optimization and voyage separation requirements for a liner shipping company. The paper provides both an arc-flow and a path-flow model, as well as three path reduction heuristic approaches, and it is shown that the path-flow model outperforms the arc-flow model.