Multimodal transportation has become a main focus of logistics systems due to environmental concerns, road safety issues, and traffic congestion. Consequently, research and policy interests in multimodal freight transportation problems are increasing. However, there are major challenges in the development of multimodal transportation associated with inherent risks and numerous uncertainties. Since risks are potential threats that directly impact logistics and transportation systems, comprehensive risk analysis should be carried out. Risk analysis is a critical process of identifying and analyzing significant issues to help industry mitigate those risks. However, identifying and prioritizing risks is more complex because of the ambiguity of the relevant data. This study proposes the integration of the fuzzy analytic hierarchy process (FAHP) and data envelopment analysis (DEA) for identifying and assessing quantitative risks. The proposed FAHP-DEA methodology uses the FAHP method to determine the weights of each risk criterion. The DEA method is employed to evaluate the linguistic variables and generate the risk scores. The simple additive weighting (SAW) method is used to aggregate risk scores under different risk criteria into an overall risk score. A case study of the coal industry demonstrates that the proposed risk analysis model is practical and allows users to more accurately prioritize risks while selecting an optimal multimodal transportation route. The process raises user's attention to the high-priority risks and is useful for industries in optimizing a multimodal transportation route under risk decision criteria. INDEX TERMS Multimodal freight transportation, logistics, optimal route, risk analysis, risk assessment, DEA, FAHP.
Route selection strategy has become the main aspect in the multimodal transportation system. The transport cost and time as well as the inherent risks must be considered when determining a corrective design plan. The selection of a multimodal transportation network route is a complex multi-objective decision problem. Therefore, considering the impact factors such as the transport cost, time, and comprehensive risk assessment model were further created. This paper develops a decision support model using an analytic hierarchy process (AHP) and zero-one goal programing (ZOGP) to determine an optimal multimodal transportation route. AHP is employed to determine weights of each factor, which rely on expert judgments. The significant weights of criteria obtained from AHP can be integrated in the objective function of ZOGP which is used to generate the optimal route. The empirical case study of coal manufacturing is conducted to demonstrate the proposed model. This methodology can provide a guidance for effectively determining the multimodal transportation routes to improve performance of logistics systems.
Organizations are a collection of individuals, and often a disastrous organizational accident involves contributions from several technical/environmental factors and actors throughout the system over time. This paper illustrates the efficiency of a new collaborative decision making technique that could assist a group of executive decision makers in identifying, analyzing, evaluating and prioritizing significant organizational system risks. The results from the collaborative technique when applied to real world risk intensive situations, such as aviation safety risk management, are compared with those obtained by using existing notable techniques. For the case examples shown, the number of expert judgments is reduced by up to 80%. Advantages and limitations of the proposed modeling approach for collaborative decision making are discussed.
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