Mathematical optimization problems that simultaneously take into account several, typically conflicting, transportation planning objectives are known as multi-objective transportation problems (MOTPs). Unlike classic transportation problems, where only one objective is taken into consideration, such as lower costs, MOTP aims to find the most effective solutions to multiple objectives simultaneously. Decision-making processes in real situations are cumbersome within transportation networks, transmission vehicles, or delivery setups. Transportation in real life cannot be portrayed in distinctly defined terms because logistical challenges are not just limited to cost alone. Based on supply, demand, and conveyance capacity, we examined a multi-choice multi-objective solid transportation problem (MC-MOSTP) in which the objective function was analyzed. The suggested model used Lagrange’s interpolation polynomial approach to deal with uncertainty, and a numerical example was used to validate the model’s applicability.