Evolutionary framework for two-stage stochastic resource allocation problems (EvFW)

The EvFW is an optimization methodology for two-stage stochastic resource allocation problems. In each iteration of EvFW, a local search algorithm selects resources to be acquired in the first stage, and then a genetic metaheuristic completes the solutions for each scenario. After each iteration, the best solution is retained and relevant information is passed on to the next iteration, supporting the acquisition of promising resources in the following first-stage.

The EvFW sourcecode can be downloaded through this link.

A case study for the EvFW applied to the two-stage stochastic Steiner tree problem can be found through this link.