Uncertainties ship operators face on a spot market
On Thursday 22 November 2018 Vit Procházka will hold a trial lecture on a prescribed topic and defend his thesis for the PhD degree at NHH.
Prescribed topic for the trial lecture:
Interface of big data and stochastic programming: Discuss what opportunities and challenges bring the big data era for the development and application of stochastic programming
10:15 in Jebsen Centre, NHH
Title of the thesis:
Uncertainty modeling and spatial positioning in tramp shipping
This thesis is inspired by a decision-making process of a ship operator trading on a spot market. The focus is on understanding and modeling of uncertainties that the operator faces – future freight rates, cargo availability, trip duration, etc. The thesis is organized in four self-containing chapters.
The first chapter investigates the contracting behavior of freight market participants in crude oil transportation. The authors empirically assess the relationship between the distance from the fixture (a vessel is hired for a voyage) location to the loading port and market conditions and vessel specifications and discuss different strategic choices that a shipowner or an operator faces.
In the second chapter, the authors estimate the upper bound for the increase in vessel earnings obtained from perfect decisions about the relocation of a vessel between regions in the drybulk freight market. The upper bound is evaluated by assuming perfect knowledge of future regional freight rates, instant cargo availability and optimization of spatial repositioning of a vessel.
The third chapter focuses on stochastic programs where uncertainty is represented by a multivariate Bernoulli (binary) distribution. This chapter introduces two simple procedures that exploit a special structure of a problem with a penalization term. This chapter is published in Computational Management Science. Although the original motivation is modeling of a presence of a future cargo in the shipping problem, the results are more general, and thus, are presented in such a way.
The fourth chapter introduces an original framework for scenario generation based on minimizing discrepancy between in-sample and out-of-sample performance of a pool of heuristically obtained solutions. The framework is not, in principle, limited to any distribution, and thus, can be applied on a mix of continuous and binary distributions, for example in modeling future cargo availability and future freight rates at the same time.
12:15 in Jebsen Centre, NHH
Members of the evaluation committee:
Assistant Professor Julio Cesar Goez (leader of the committee), Department of Business and Management Science, NHH
Professor Zhaoxia Guo, Sichuan University
Assistant Professor Francesca Maggioni, University of Bergamo
Professor Stein W. Wallace (main supervisor), Department of Business and Management Science, NHH
Professor Roar Os Ådland, Department of Business and Management Science, NHH
Professor François-Charles Wolff, University in Nantes
The trial lecture and thesis defence will be open to the public. Copies of the thesis will be available from email@example.com