Many studies have developed mathematical programming models for optimal design of supply chains for agricultural or lingocellulosic biomass-derived bioethanol production. However, because of the shortcomings of using agricultural (food supply problems) and lingo-cellulosic biomass (low biomass availability and processing yield) as feedstock, use of micro-algal biomass has been considered for use as a feedstock for biodiesel (biofuel). Thus, in this study we developed a deterministic mathematical programming model for strategic planning design of a microalgae biomass-to-biodiesel supply chain network (MBBSCN) from feedstock fields to end users that simultaneously satisfies resource constraints, demand constraints, and technology over a long-term planning horizon. The proposed deterministic model can help to determine where and how much feedstock to be transported, and where and how many refineries to be constructed to minimize the expected total cost including the co-product (naphtha and power) benefit. To demonstrate the feasibility of the proposed model, we conducted a case study based on the Korea biodiesel market data. In this case study, the optimized (i.e., most cost-effective) supply chain design can be gained at a reliable cost of similar to$US 5.91/gal ($US 1.56/1). In particular, this study can help to identify the technological bottlenecks and major cost drivers for the microalgae-to-diesel strategy, and can be also a guideline for development of various mathematical programming models for optimal design of microalgae biomass-derived biofuel supply chain like lingo-cellulosic biomass-based optimization studies. (C) 2015 Elsevier Ltd. All rights reserved.