ENERGY EFFICIENT SHIP VOYAGE PLANNING BY 3D DYNAMIC PROGRAMMING

Energy efficiency is a crucial issue in ship management and operation. A proper fuel saving oriented routing strategy can be helpful in reducing running costs and pollutant emissions, as well as increasing the voyage safety and comfort. This paper presents a methodology for ship voyage planning based on 3D dynamic programming. It aims to select the optimum courses and related speed profile for a ship voyage in accordance to a minimum fuel consumption strategy, on the basis of the ship response to wave and wind conditions inferred from weather forecast maps. The ship voyage is parametrized as a multi-stage decision process where the fuel optimization is carried out in a discretized space-time domain and the optimal solution, in relation to the arrival time requirements and motion related constraints, is found by a dynamic programming algorithm which has been developed and implemented by the authors. Simulation trials for a merchant ship sailing different typical routes in the Mediterranean Sea, in a wide range of weather conditions and using high quality weather forecast maps, are presented and discussed. With respect to previous authors\u2019 publications, the presented methodology shows the high potential benefit of detailed weather forecast maps as well as the innovative use of a minimum distance algorithm

Obtaining Optimal Mobile-Robot Paths with Non-Smooth Anisotropic Cost Functions Using Qualitative-State Reasoning

This paper appeared in the International Journal of Robotics Research, 16, 3 (June 1997), 375-399. The equations were reconstructed in 2007 for better readability.Realistic path-planning problems frequently show anisotropism, dependency of traversal cost or feasibility on the traversal heading. Gravity, friction, visibility, and safety are often anisotropic for mobile robots. Anisotropism often differs qualitatively with heading, as when a vehicle has insufficient power to go uphill or must brake to avoid accelerating downhill. Modeling qualitative distinctions requires discontinuities in either the cost-per-traversal-distance function or its derivatives, preventing direct application of most results of the calculus of variations. We present a new approach to optimal anisotropic path planning that first identifies qualitative states and permissible transitions between them. If the qualitative states are chosen appropriately, our approach replaces an optimization problem with such discontinuities by a set of subproblems without discontinuities, subproblems for which optimization is likely to be faster and less troublesome. Then the state space in the near neighborhood of any particular state can be partitioned into "behavioral regions" representing states optimally reachable by single qualitative "behaviors", sequences of qualitative states in a finite-state diagram. Simplification of inequalities and other methods can find the behavioral regions. Our ideas solve problems not easily solvable any other way, especially those with what we define as "turn-hostile" anisotropism. We illustrate our methods on two examples, navigation on an arbitrarily curved surface with gravity and friction effects (for which we show much better performance than a previously-published program 22 times longer), and flight of a simple missile.This work was supported in part by the U.S. Army Combat Developments Experimentation Center under MIPR ATEC 88-86. This work was also prepared in part in conjunction with research conducted for the Naval Air Systems Commandfunded by the Naval Postgraduate SchoolApproved for public release; distribution is unlimited

Applied Model-Based Analysis and Synthesis for the Dynamics, Guidance, and Control of an Autonomous Undersea Vehicle

Model-based analysis and synthesis applied to the dynamics, guidance, and control of an autonomous undersea vehicle are presented. As the dynamic model for describing vehicle motion mathematically, the equations of motion are derived. The stability derivatives in the equations of motion are determined by a simulation-based technique using computational fluid dynamics analysis. The dynamic model is applied to the design of the low-level control systems, offering model-based synthetic approach in dynamics and control applications. As an intelligent navigational strategy for undersea vehicles, we present the optimal guidance in environmental disturbances. The optimal guidance aims at the minimum-time transit of a vehicle in an environmental flow disturbance. In this paper, a newly developed algorithm for obtaining the numerical solution of the optimal guidance law is presented. The algorithm is a globally working procedure deriving the optimal guidance in any deterministic environmental disturbance. As a fail-safe tactic in achieving the optimal navigation in environments of moderate uncertainty, we propose the quasi-optimal guidance. Performances of the optimal and the quasi-optimal guidances are demonstrated by the simulated navigations in a few environmental disturbances

A multiple ship routing and speed optimization problem under time, cost and environmental objectives

The purpose of this paper is to investigate a multiple ship routing and speed optimization problem under time, cost and environmental objectives. A branch and price algorithm as well as a constraint programming model are developed that consider (a) fuel consumption as a function of payload, (b) fuel price as an explicit input, (c) freight rate as an input, and (d) in-transit cargo inventory costs. The alternative objective functions are minimum total trip duration, minimum total cost and minimum emissions. Computational experience with the algorithm is reported on a variety of scenarios. © 2017 Elsevier Lt

Πορεία δρομολόγησης πλοίου : weather routing

Κοινή εργασία σε δύο διαφορετικές εκδόσεις με ίδιο περιεχόμενο - αντιστοιχισμένες με συγγραφέα. Διαφέρει μόνο η σελίδα τίτλου

Autonomous Sailboat Navigation

The purpose of this study was to investigate novel methods on an unmanned sailing boat, which enables it to sail fully autonomously, navigate safely, and perform long-term missions. The author used robotic sailing boat prototypes for field experiments as his main research method. Two robotic sailing boats have been developed especially for this purpose. A compact software model of a sailing boat's behaviour allowed for further evaluation of routing and obstacle avoidance methods in a computer simulation. The results of real-world experiments and computer simulations are validated against each other. It has been demonstrated that autonomous boat sailing is possible by the effective combination of appropriate new and novel techniques that will allow autonomous sailing boats to create appropriate routes, to react properly on obstacles and to carry out sailing manoeuvres by controlling rudder and sails. Novel methods for weather routing, collision avoidance, and autonomous manoeuvre execution have been proposed and successfully demonstrated. The combination of these techniques in a layered hybrid subsumption architecture make robotic sailing boats a promising tool for many applications, especially in ocean observation

Barge Prioritization, Assignment, and Scheduling During Inland Waterway Disruption Responses

Inland waterways face natural and man-made disruptions that may affect navigation and infrastructure operations leading to barge traffic disruptions and economic losses. This dissertation investigates inland waterway disruption responses to intelligently redirect disrupted barges to inland terminals and prioritize offloading while minimizing total cargo value loss. This problem is known in the literature as the cargo prioritization and terminal allocation problem (CPTAP). A previous study formulated the CPTAP as a non-linear integer programming (NLIP) model solved with a genetic algorithm (GA) approach. This dissertation contributes three new and improved approaches to solve the CPTAP. The first approach is a decomposition based sequential heuristic (DBSH) that reduces the time to obtain a response solution by decomposing the CPTAP into separate cargo prioritization, assignment, and scheduling subproblems. The DBSH integrates the Analytic Hierarchy Process and linear programming to prioritize cargo and allocate barges to terminals. Our findings show that compared to the GA approach, the DBSH is more suited to solve large sized decision problems resulting in similar or reduced cargo value loss and drastically improved computational time. The second approach formulates CPTAP as a mixed integer linear programming (MILP) model improved through the addition of valid inequalities (MILP\u27). Due to the complexity of the NLIP, the GA results were validated only for small size instances. This dissertation fills this gap by using the lower bounds of the MILP\u27 model to validate the quality of all prior GA solutions. In addition, a comparison of the MILP\u27 and GA solutions for several real world scenarios show that the MILP\u27 formulation outperforms the NLIP model solved with the GA approach by reducing the total cargo value loss objective. The third approach reformulates the MILP model via Dantzig-Wolfe decomposition and develops an exact method based on branch-and-price technique to solve the model. Previous approaches obtained optimal solutions for instances of the CPTAP that consist of up to five terminals and nine barges. The main contribution of this new approach is the ability to obtain optimal solutions of larger CPTAP instances involving up to ten terminals and thirty barges in reasonable computational time

Stability and Seakeeping of Marine Vessels

This book presents the papers accepted into the Special Issue “Stability and Seakeeping of Marine Vessels” and includes nine contributions to this Special Issue published in 2020. The overall aim of the collection is to improve knowledge about the most relevant and recent topics in ship stability and seakeeping. Specifically, the articles cover a wide range of topics and reflect the recent scientific efforts in the 2nd generation intact stability criteria evaluation and modelling of the ship dynamics assessment in intact or damaged conditions. These topics were investigated mainly through direct assessments performed both via numerical methods and tools, and experimental approaches. The book is addressed to individuals from universities, research organizations, industry, government agencies and certifying authorities, as well as designers, operators and owners who contribute to improved knowledge about “stability and seakeeping”

Optimal ship routing

Thesis (Nav. E. and S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (p. 114-118).Fuel savings in ship navigation has always been a popular subject in the maritime industry as well as the world's largest Navies. Oil prices and environmental considerations drive the effort for more fuel-efficient navigation. This thesis addresses the problem of deterministic minimum fuel routing by applying optimal control theory in conjunction with state of the art hydrodynamic and weather forecasting tools. A fictitious trans-Atlantic route is established and the optimal combination of speed and heading is determined, so that fuel consumption is minimized while certain safety constraints are met. The safety constraints are defined as the probabilities of slamming and deck wetness, both of which are not allowed to exceed prescribed limiting values. The problem formulation adopted in the thesis lies in the framework of Dynamic Programming, which is most suitable for computer implementation. The hydrodynamic performance of the ship is computed through the use of SWAN1, an advanced frequency domain CFD code. With the aid of SWAN1, ship motions and resistance can be accurately calculated. The latter includes the estimation of mean added resistance in waves, which has a major effect on the fuel consumption of ships sailing in rough seas. Wave and swell forecasts are provided in a deterministic setting by a third generation numerical wave model, the WAM cycle 4, developed at the European Center for Medium-Range Weather Forecasts (ECMWF). Utilizing the hydrodynamic results and the output of the wave model a computer program is developed in MATLAB®, which employs the Iterative Dynamic Programming algorithm to solve the optimal control problem.by Kyriakos Avgouleas.Nav.E.and S.M