Decisions regarding investments in capacity expansion/renewal require taking into account both the operating fitness and the financial performance of the investment. While several operating requirements have been considered in the operations research literature, the corresponding financial aspects have not received as much attention. We introduce a model for the renewal of shipping capacity which maximizes the Average Internal Rate of Return (AIRR). Maximizing the AIRR sets stricter return requirements on money expenditures than classic profit maximization models and may describe more closely shipping investors׳ preferences. The resulting nonlinear model is linearized to ease computation. Based on data from a shipping company we compare a profit maximization model with an AIRR maximization model. Results show that while maximizing profits results in aggressive expansions of the fleet, maximizing the return provides more balanced renewal strategies which may be preferable to most shipping investors.
This paper addresses the fleet renewal problem and particularly the treatment of uncertainty in the maritime case. A stochastic programming model for the maritime fleet renewal problem is presented. The main contribution is that of assessing whether or not better decisions can be achieved by using stochastic programming rather than employing a deterministic model and using average data. Elements increasing the relevance of uncertainty are also investigated. Tests performed on the case of Wallenius Wilhelmsen Logistics, a major liner shipping company, show that solutions to the model we present perform noticeably better than solutions obtained using average values.