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A piano fingering indicates which finger should play each note in a piece. Such a guideline is very helpful for both amateur and experienced players in order to play a piece fluently. In this paper, we propose a variable neighborhood search algorithm to generate piano fingerings for complex polyphonic music, a frequently encountered case that was ignored in previous research. The algorithm takes into account the biomechanical properties of the pianist's hand in order to generate a fingering that is user‐specific and as easy to play as possible. An extensive statistical analysis was carried out in order to tune the parameters of the algorithm and evaluate its performance. The results of computational experiments show that the algorithm generates good fingerings that are very similar to those published in sheet music books.

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Objective: The existing literature on the application of real options in maritime economics is rather limited. Bendall & Stent (2003, 2005, 2007 show how investing in a new ship or maritime technology can incorporate an option value. Another application is elaborated by Bjerksund & Ekern (1995), discussing the value of mean-reverting cash flows through contingent claim analysis, applied to time charters. The analysis of the entry and exit decision in the shipping markets can form an interesting extension of this research. Shipping markets are in nature uncertain and cyclical (Stopford, 2009). For this reason, the real options based model of Ruiz-Aliseda & Wu (2012) for stochastically cyclical markets will be applied to the shipping markets, in order to define entry and exit thresholds in this market.Data/Methodology: Data on the freight rates, costs and ship prices are used for estimating the parameters present in the real options based model of Ruiz-Aliseda & Wu (2012) for stochastically cyclical markets. This model incorporates a discrete-time Markov process, an alternative for the traditionally used geometric Brownian motion (GBM) and suited to model the cyclicality of the shipping markets. Investing in a ship and selling it again can respectively be interpreted as entering and exiting the market. Hence, the model can be applied here in order to predict the optimal values for entry and exit in the shipping markets.Results/Findings: The theoretically calculated results will be tested on real cases using data on container time charter prices over different periods, to see how well the theoretically developed model performs in the shipping markets. In that way, the estimation of parameters and the assumptions of the model can be evaluated on their accuracy in these cyclical markets.Implications for Research/Policy: In the first place, this case study can indicate how well the model performs in another market. If the model turns out to successfully predict market entry and exit thresholds, it could help companies to make better predictions on competitor behaviour. Also for policy makers, it could help to have a more accurate insight in the required capacity for ports.

In this paper, the efficiency of the major US all-cargo carriers, both integrated and non-integrated, is measured and compared through a stochastic frontier analysis based on a translog cost function. Because of the high volatility of all-cargo traffic, especially since the 2008 economic crisis, and the increasing market share of integrators, this industry requires more detailed analysis. By using stochastic frontier analysis in this study, a distinction between random deviations from the production frontier and actual differences in technical efficiency is made. We find that smaller carriers react more flexible to a crisis and that non-integrated carriers are more efficient than the integrators when they are analysed jointly, which is however complicated by their different business models. These findings are not only useful for academics and industry actors, but also for policy makers, since air cargo contributes significantly to the profitability of airlines and airports.