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While many previous studies have suggested well-defined procedures to find appropriate supply chains, a limited number of studies have been conducted with uncertain values relating to transportation costs. Most of these have included only limited detail on multimodal transportation, or have not considered economic, social, and environmental transportation cost factors together. The main purpose of this study is to suggest a multi-objective stochastic model for sustainable biomass transportation, and to identify the impact level of model selection on the transportation mode. It begins with a deterministic formulation of sustainable transportation, which is then modified to a stochastic problem with vectorization of cost parameters. Based on the model developed, we examined four uncertainty cases from a combination of annual capacity and average distance of biomass transportation. The experimental results provide more cost savings from multimodal transportation, which can be identified if we analyze transportation costs with stochastic modeling. Regarding short-distance plant cases, the study reveals that the impact of the utilization of stochastic methods is insignificant, as the costs savings from multimodal transportation is trivial. Other findings from the experiments show that multimodal transportation could provide cost savings in the economic cost factor, except in the case of low annual capacity and short average distance.

A Stochastic Optimization Model for Sustainable Multimodal Transportation for Bioenergy Production