Abstract
The methodology developed through this PhD thesis entitled “Ship Design Optimization in the Context of an Integrated System for Multimodal Transport” is dedicated to the identification of the optimum ship design for one or multiple sea routes, when considering the multimodal door to door transport. The objective is to incorporate feasibility study, routing, fleet management, ship design, environmental assessment and economic analysis into one integrated methodology which is able to produce efficiently the Pareto Front of optimal solutions for the set multiobjective-multicriteria transport problem. The methodology is supported by automated software. Demand analysis is implemented by the use of statistical data, in order to estimate the cargo flow in the multimodal network. This is a crucial point which is considered separately. Moreover, the method includes a risk assessment and sensitivity analysis of the solutions, confronting demand uncertainty in a most secure way and further, intro ...
The methodology developed through this PhD thesis entitled “Ship Design Optimization in the Context of an Integrated System for Multimodal Transport” is dedicated to the identification of the optimum ship design for one or multiple sea routes, when considering the multimodal door to door transport. The objective is to incorporate feasibility study, routing, fleet management, ship design, environmental assessment and economic analysis into one integrated methodology which is able to produce efficiently the Pareto Front of optimal solutions for the set multiobjective-multicriteria transport problem. The methodology is supported by automated software. Demand analysis is implemented by the use of statistical data, in order to estimate the cargo flow in the multimodal network. This is a crucial point which is considered separately. Moreover, the method includes a risk assessment and sensitivity analysis of the solutions, confronting demand uncertainty in a most secure way and further, introduces sacrifice functions to serve decision making. Artificial Neural Networks (ANNs) are trained and integrated in the method to create an initial estimation for the main particulars of the design, taking into consideration the broader business concept. The number of ships, the routing and respective demand/market share, the frequency of the service and the ship’s specification are some of the variables used in the proposed methodology. The optimization problem encompasses three main criteria (objective functions): Door-to-Door (D2D) time, Through Freight Rate (TFR) and Door-to- Door-CO2 emissions. The minimization of TFR is achieved by the optimization of the ship system scenario but also by the ship design optimization for least resistance and powering. The overall method is broken down into five main stages, other than the demand analysis: the Transport System Development, the Ship Design Development (Preliminary Design Study & Optimization), the Economic Analysis, the Environmental Assessment and the Performance Assessment. The approach is illustrated by means of a case study related to transportation of goods from the Greek island of Crete to the markets of Italy and Munich. The project ventures the introduction of a direct sea connection from Crete to Italy with or without an intermediate port node, by the use of multimodal transport. Finally, in another application for the same market all variables are activated enabling also the investigation of different route paths in each direction. The outcomes of this study prove essential for the assessment of a sea route which has been traditionally considered unprofitable and further implies the benefits of an overall scientific approach which replaces guess estimates and one sided investigation.The methodology developed through this PhD thesis entitled “Ship Design Optimization in the Context of an Integrated System for Multimodal Transport” is dedicated to the identification of the optimum ship design for one or multiple sea routes, when considering the multimodal door to door transport. The objective is to incorporate feasibility study, routing, fleet management, ship design, environmental assessment and economic analysis into one integrated methodology which is able to produce efficiently the Pareto Front of optimal solutions for the set multiobjective-multicriteria transport problem. The methodology is supported by automated software. Demand analysis is implemented by the use of statistical data, in order to estimate the cargo flow in the multimodal network. This is a crucial point which is considered separately. Moreover, the method includes a risk assessment and sensitivity analysis of the solutions, confronting demand uncertainty in a most secure way and further, introduces sacrifice functions to serve decision making. Artificial Neural Networks (ANNs) are trained and integrated in the method to create an initial estimation for the main particulars of the design, taking into consideration the broader business concept. The number of ships, the routing and respective demand/market share, the frequency of the service and the ship’s specification are some of the variables used in the proposed methodology. The optimization problem encompasses three main criteria (objective functions): Door-to-Door (D2D) time, Through Freight Rate (TFR) and Door-to- Door-CO2 emissions. The minimization of TFR is achieved by the optimization of the ship system scenario but also by the ship design optimization for least resistance and powering. The overall method is broken down into five main stages, other than the demand analysis: the Transport System Development, the Ship Design Development (Preliminary Design Study & Optimization), the Economic Analysis, the Environmental Assessment and the Performance Assessment. The approach is illustrated by means of a case study related to transportation of goods from the Greek island of Crete to the markets of Italy and Munich. The project ventures the introduction of a direct sea connection from Crete to Italy with or without an intermediate port node, by the use of multimodal transport. Finally, in another application for the same market all variables are activated enabling also the investigation of different route paths in each direction. The outcomes of this study prove essential for the assessment of a sea route which has been traditionally considered unprofitable and further implies the benefits of an overall scientific approach which replaces guess estimates and one sided investigation.
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