A multi-objective mixed integer linear programming model is developed to support supply chain design and planning decisions with societal goals. The developed model is built based on ToBLoOM, a Triple Bottom Line Optimization Modeling tool. Decisions include which suppliers to select, where to locate supply chain facilities and with how much capacity, which manufacturing technologies to select, where and how much inventory should be kept, which transportation network to establish and with which product flows. The model is applied to a representative European case-study evidencing its validity and applicability. Socio-economic indicators are selected based on the case-study regional context with the overall goal of contributing to the sustainability of a larger economic system – the European Union -, through the promotion of increased socio-economic equity. The following three socio-economic indicators are applied: an indicator accounting for direct job creation, as commonly found in the literature; a Gross Domestic Product-based indicator, and an Unemployment Rate-based indicator, proposed in this work. A Net Present Value objective function is also implemented to measure the supply chain economic performance. The trade-offs between the results obtained using the three socio-economic indicators and the economic performance of the supply chain are assessed. Results allow to conclude on the significant difference in supply chain decisions obtained using different socio-economic indicators. Given the subjectivity and uncertainty accompanying the attribution of weights to the different socio-economic indicators, and the significant computational time involved in the solution of the model, a new solution approach for the multi-objective problem is developed supported by a simple heuristic.