Article ID: | iaor20012851 |
Country: | United Kingdom |
Volume: | 8C |
Issue: | 1/6 |
Start Page Number: | 337 |
End Page Number: | 359 |
Publication Date: | Feb 2000 |
Journal: | Transportation Research. Part C, Emerging Technologies |
Authors: | Batta Rajan, Thill Jean-Claude, Frank William C. |
Keywords: | artificial intelligence: decision support, vehicle routing & scheduling |
Shipping hazardous material (hazmat) places the public at risk. People who live or work near roads commonly traveled by hazmat trucks endure the greatest risk. Careful selection of roads used for a hazmat shipment can reduce the population at risk. On the other hand, a least time route will often consist of urban interstate, thus placing many people in harm's way. Route selection is therefore the process of resolving the conflict between population at risk and efficency considerations. To assist in resolving this conflict, a working spatial decision support system (SDSS) called Hazmat Path is developed. The proposed hazmat routing SDSS overcomes three significant challenges, namely handling a realistic network, offering sophisticated route generating heuristics and functioning on a desktop personal computer. The paper discusses creative approaches to data manipulation, data and solution visualization, user interfaces, and optimization heuristics implemented in Hazmat Path to meet these challenges.