Using MAP-Elites to support policy making around Workforce Scheduling and Routing
AbstractAlgorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be useful when formulating policy around the problem itself. The number of solutions that can potentially be returned by MAP-Elites is controlled by a parameter d that discretises the user-defined features into ‘bins’. For a fixed evaluation budget, increasing the number of bins increases user-choice, but at the same time, may lead to a reduction in overall quality of solutions. We undertake a study of the application of Map-Elites to a Workforce Scheduling and Routing problem, using a set of realistic instances based in London.