Financial and Managerial Benchmark Problems for Nature Inspired Intelligence

The presence of benchmark problems provides an important stimulus in fields related to the development of new methodologies. Currently, benchmark data for nature-inspired networks are scarce. To increase the collection of benchmark data, we propose, in this work, a number of interesting and rather difficult managerial and financial decision problems that can be found in the literature. Usually, similar problems are addressed by methodologies belonging to statistics, operations research, mathematical programming, heuristic algorithm implementation, and classical artificial intelligence. We believe that nature inspired intelligence constitutes a challenging alternative for handling these problems effectively. For this reason, we collect formal problem descriptions, related data collections, presentation of existing solutions and comparison of the performance obtained by nature inspired approaches to other existing methodologies.