A Methodology of Network Modeling of Risk Prioritization in Hazardous Product Transportation The Analytic Network Process (ANP) has been widely researched to choose the best alternative. However, it seems that no one shows interest in using such analytical process in developing the network design on ANP analysis for more accurate results. This paper presents the application of the Design Structure Matrix (DSM) and ANP techniques to develop a methodology that can make a precise network. The preliminary analysis of ANP proves that if the default network is correct, the result will be right as well. The application in this case study is on the transportation of hazardous products. The network designed can be analyzed with ANP to find suitable alternatives for creating a risk management plan, e.g. risk prioritization on transportation system development.

An Improved BiObjective Stochastic Model with SAAbased Solution Method for Reverse Logistics Design of Hazardous Materials Nowadays, the unprecedented advancement in technology and rapid development of economy have not only brought opportunities for improving peopleu0027s living standards but also resulted in a tremendous increase on waste generation. The treatment of hazardous materials from both industrial sectors and households has become one of the most significant challenges in waste management. Because of the negative impact on the environment and the safety issues posed to the nearby residents, the design of a hazardous material management system is, however, a complicated decisionmaking problem. Thence, an improved biobjective stochastic model is proposed to design a singleproduct multistage reverse logistics system for hazardous materials under uncertainties from different input information. Moreover, a sample average approximation (SAA) based solution method is also proposed so as to find out the Pareto optimal solutions to the model under a stochastic environment. The results of the numerical experimentations illustrate the tradeoff between economic efficiency and system risk in reverse logistics design of hazardous materials. In addition, the impact from uncertainties related to the input information is also revealed.