The United States Navy Meteorology and Oceanography (METOC) community routes ships for weather evasion using advanced meteorological modeling and satellite data, but lacks a tool to enable fewer ship routers to make better routing decisions faster. Limited resources and rising costs are impacting the frequency and duration of current naval operations. The Commander, Naval Meteorology and Oceanography Command has ordered the community to find efficiencies and automation possibilities in order to meet lower manning levels, reduce waste, and increase savings. Outside of the Navy, Ocean Systems Incorporated in Alameda, CA developed the Ship Tracking and Routing System (STARS) software package to calculate optimum sea routes based on weather model data. However, METOC ship routers are reluctant to adopt this complex software. To help solve this, we modeled Optimum Track Ship Routing (OTSR) for U.S. Navy warships using a network graph of the Western Pacific Ocean. A binary heap version of Dijkstra's algorithm determines the optimum route given model generated wind and seas input. We test the model against recent weather data to verify the model's performance, and to historical divert route recommendations in order to validate against routes developed by OTSR personnel.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, March 2008. / Thesis Advisor(s): Wood, R. Kevin. "March 2008." Includes bibliographical references (p. 37-38). Also available online.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2005. / Thesis Advisor(s): Gerald G. Brown. Includes bibliographical references (p. 73-74). Also available online.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2005. / I. A. Karimi, Committee Member ; Shabbir Ahmed, Committee Member ; Faiz Al-Khayyal, Committee Chair Chelsea (Chip) C. White III, Committee Member ; Earl Barnes, Committee Member. Includes bibliographical references.

Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2007. / Committee Chair: Al-Khayyal, Faiz; Committee Member: Barnes, Earl; Committee Member: Johnson, Ellis; Committee Member: Karimi, IA; Committee Member: Sokol, Joel.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008. / Professor Michael D. Meyer, Committee Member ; Professor Ozlem Ergun, Committee Chair ; Professor Ellis Johnson, Committee Member ; Professor George L. Nemhauser, Committee Member ; Professor H. Venkateswaran, Committee Member.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Ocean Engineering, 1978 / Includes bibliographical references. / by H.T. Chen. / Ph. D. / Ph. D. Massachusetts Institute of Technology, Department of Ocean Engineering

In maritime transportation, liner shipping accounts for over 60\% of the value of goods shipped. However, very limited literature is available on the study of various problems in liner shipping. In this thesis we focus on problems related to this industry. Given a set of cargo to be transported, a set of ports and a set of ships, a common problem faced by carriers in liner shipping is the design of their service network. We develop an integrated model to design service network for the ships and to route the available cargo, simultaneously. The proposed model incorporates many relevant constraints, such as the weekly frequency constraint on the operated routes, and emerging trends, such as obtaining benefits from transshipping cargo on two or more service routes, that appear in practice but have not been considered previously in literature. Also, we design exact and heuristic algorithms to solve the integer program efficiently. The proposed algorithms integrate the ship scheduling problem, a tactical planning level decision, and the cargo routing problem, an operational planning level decision, and provide good overall solution strategy. Computational experiments indicate that larger problem instances, as compared to the literature, can be solved using these algorithms in acceptable computational time. Alliance formation is very common among global liner carriers however a quantitative study of liner alliances is missing from literature. We provide a mathematical framework for the quantitative study of these alliances. For the formation of a sustainable alliance, carriers need to agree on an overall service network and resolve issues concerning distribution of benefits and costs among the members of the alliance. We develop mechanisms to design a collaborative service network and to manage the interaction among the carriers through the allocation of profits in a fair way. The mechanism utilizes inverse optimization techniques to obtain resource exchange costs in the network. These costs provide side payments to the members, on top of the revenue generated by them in the collaborative solution, to motivate them to act in the best interest of the alliance while satisfying their own self interests.

This thesis introduces a new model formulation to solve routing and scheduling problems, with the main applications in answering routing and scheduling problems faced by a sea-cargo shipping company and a railroad company. For the work in sea-cargo routing and scheduling, we focus on the tramp shipping operation. Tramp shipping is a demand-driven type of shipping operation which does not have fixed schedules. The schedules are based on the pickup and download locations of profitable service requests. Given set of products distributed among a set of ports, with each product having pickup and download time windows and a destination port, the problem is to find the schedule for a fleet of ships that maximizes profit over a specified time horizon. The problem is modeled as a Mixed Integer Non-Linear Program and reformulated as an equivalent Mixed Integer Linear Program. Three heuristic methods, along with computational results, are presented. We also exploit the special structure enjoyed by our model and introduce an upper-bounding problem to the model. With a little modification, the model is readily extendable to reflect soft time windows and inter-ship cargo-transfers. The other part of our work deals with train routing and scheduling. A typical train shipment consists of a set of cars having a common origin and destination. To reduce the handling of individual shipments as they travel, shipments are grouped into blocks. The problem is that given sets of blocks to be carried from origins to destinations, construct the most cost effective train routes and schedules and determine block-to-train assignments, such that the number of block transfers (block swaps) between trains, the number of trains used, and some other cost measures are minimized. Incorporating additional precedence requirements, the modeling techniques from the shipping research are employed to formulate a mixed integer nonlinear program for this train routing and scheduling problem. Computational results are presented.