Dynamic Decision Making Process for Dangerous Good Transportation Using a Combination of TOPSIS and AHP Methods With Fuzzy Sets

Abstract

Dangerous Goods Transportation in smart cities is one of the most intriguing topics that researchers are interested in to reduce the risks caused by hazardous events. This article proposes a novel technique to avoid hazardous events during the transportation of dangerous goods using real-time information provided by the cloud. This article applies Fuzzy Analytical Hierarchy Process - Technique for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) hybrid method for risk analysis applied to Dangerous goods transportation in a smart city. The article assumes that we have three criteria that dictate the choice of routs the vehicle follows: cost, duration, and risk. The main objective is to choose the best route through calculated weights assigned to the three criteria based on predefined pairwise comparisons. The study is done on both static and dynamic environments. In static environments, the decision is made and is followed prior to actions and no change of actions is made even if criteria values change. In dynamic environments on the other hand, the decision could change during the transportation process due to the change of the valuation the criteria contribute to. The study shows that risk is reduced and therefore safety is increased for the transportation of dangerous goods.

Keywords

• Supply chains
• industry 40
• best trajectory identification
• dangerous good transportation
• fuzzy AHP
• fuzzy TOPSIS