The efficient design of supply chains incorporating ecological objectives is a strategic task that is increasingly attracting the attention of companies. This paper introduces a simulation-based optimization approach to eco-efficiently orchestrate a supply chain with a target system consisting of three sub-targets: Costs, energy-efficiency and service level. Regarding a use case from the steel processing industry, an event-discrete simulation model of the corresponding supply chain was configurated. By interfacing the simulation model with a Nondominated Sorting Genetic Algorithm new configurations of decision variables are generated after a set of simulation runs. The evaluation of the experiments and the resulting pareto sets led to the identification of promising eco-efficient configurations and the derivation of corresponding decision variable assignments for the use case which consist of material allocation, reorder point and replenishment level.