This thesis provides a `proof-of-concept' prototype and a design architecture for a
Object Oriented (00) database towards the development of a Decision Support
System (DSS) for the national freight transport planning problem. Both governments
and industry require a Strategic Planning Extranet Decision Support System
(SPEDSS) for their effective management of the national Freight Transport Networks
This thesis addresses the three key problems for the development of a SPEDSS to
facilitate national strategic freight planning: 1) scope and scale of data available and
required; 2) scope and scale of existing models; and 3) construction of the software.
The research approach taken embodies systems thinking and includes the use of:
Object Oriented Analysis and Design (OOA/D) for problem encapsulation and
database design; artificial neural network (and proposed rule extraction) for
knowledge acquisition of the United States FTN data set; and an iterative Object
Oriented (00) software design for the development of a `proof-of-concept'
prototype. The research findings demonstrate that an 00 approach along with the use
of 00 methodologies and technologies coupled with artificial neural networks
(ANNs) offers a robust and flexible methodology for the analysis of the FTN problem
domain and the design architecture of an Extranet based SPEDSS.
The objectives of this research were to: 1) identify and analyse current problems and
proposed solutions facing industry and governments in strategic transportation
planning; 2) determine the functional requirements of an FTN SPEDSS; 3) perform a
feasibility analysis for building a FTN SPEDSS `proof-of-concept' prototype and
(00) database design; 4) develop a methodology for a national `internet-enabled'
SPEDSS model and database; 5) construct a `proof-of-concept' prototype for a
SPEDSS encapsulating identified user requirements; 6) develop a methodology to
resolve the issue of the scale of data and data knowledge acquisition which would act
as the `intelligence' within a SPDSS; 7) implement the data methodology using
Artificial Neural Networks (ANNs) towards the validation of it; and 8) make recommendations for national freight transportation strategic planning and further
research required to fulfil the needs of governments and industry.
This thesis includes: an 00 database design for encapsulation of the FTN; an
`internet-enabled' Dynamic Modelling Methodology (DMM) for the virtual
modelling of the FTNs; a Unified Modelling Language (UML) `proof-of-concept'
prototype; and conclusions and recommendations for further collaborative research
A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.