  In this paper, a green transportation location problem is considered with
uncertain demand parameter. Increasing robustness influences the number of
trucks for sending goods and products, and consequently, makes the air
pollution enhance. In this paper, two green approaches are introduced which
demand is the main uncertain parameter in both. These approaches are addressed
to provide a trade-off between using available trucks and buying new hybrid
trucks for evaluating total costs besides air pollution. Due to growing
complexity, a Lagrangian decomposition algorithm is applied to find a tight
lower bound for each approach. In this propounded algorithm, the main model is
decomposed into master and subproblems to speed up convergence with a tight
gap. Finally, the suggested algorithm is compared with commercial solver
regarding total cost and computational time. Due to computational results for
the proposed approach, the Lagrangian decomposition algorithm is provided a
close lower bound in less time against commercial solver.
