1. A computer-implemented method of optimizing a supply chain, comprising: a) generating, by operation of one or more processors executing a first application, an optimized production solution for the supply chain by using a genetic algorithm optimization technique to optimize a population of seed solutions, wherein the optimized production solution specifies at least, for each day of an optimization period: (i) a production level for each of one or more commodity products produced at each of one or more production plants and (ii) a production split between the commodity products for each of the one or more production plants; and b) generating, by operation of one or more processors executing a second application, an optimized distribution solution for distributing the commodity products produced according to the optimized production solution using an ant colony optimization technique, wherein generating the optimized distribution solution for the optimized production solution using the ant colony optimization technique, comprises: (i) initializing a plant weight vector for each of the production plants in the supply chain, wherein components of the plant weight vector indicate preferences for a delivery from the plant represented by the plant weight vector to an installation represented by a vector component, (ii) initializing an installation vector for each delivery location in the supply chain, and wherein components of installation vector indicate a preference for a subsequent delivery from the installation represented by the installation vector to an installation represented by a vector component, and (iii) generating the distribution solution based on a set of weights specified by components of the plant weight vectors and installation vectors, wherein the distribution solution describes one or more delivery routes from a given one of the production plants to at least one delivery location.