Loading...
Please wait, while we are loading the content...
Similar Documents
Expert System for Selection of Network-based Transportation Planning Software Packages
| Content Provider | Semantic Scholar |
|---|---|
| Author | Safwat, K. Nabil Ali El-Araby, Khaled |
| Copyright Year | 1990 |
| Abstract | The rapid proliferation of microcomputer software packages for network-based transportation planning, with different capabilities and limitations, makes it difficult to evaluate and select a package to satisfy the needs and constraints of a particular agency or transportation planner. The software selection process is complex because it involves a multi-objective decision-making process with ill-defined tradeoffs between the objectives as well as the capabilities and limitations of alternative packages. An expert system is described to assist practicing transportation planners and engineers in selecting microcomputer packages for network-based transportation planning to satisfy their agencies' needs and constraints. The Network-Based Transportation Planning Software Selection Advisor (NETSSA) is implemented in LISP on a VAX computer. NETSSA is highly interactive and user friendly. Its current knowledge base includes nine software packages; however, it can easily be expanded by its developers to include additional software packages and/or heuristics. The advice provided by NETSSA is supported with full explanation and reasoning. The user can accept it in whole or in part. NETSSA allows the user to change the relative weights placed on the different aspects and options, assign new weights, and declare specific requirements as being absolutely critical to the user. These flexibilities enable the user to use NETSSA interactively until he or she arrives at a recommendation that would optimally satisfy his or her agency's "realistic" needs and constraints. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://onlinepubs.trb.org/Onlinepubs/trr/1990/1283/1283-011.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |