Applying a slime mold-inspired algorithm to network planning challenges in the Carinthian region

Abstract

This article presents the application of the slime mold-based algorithm Simulation of Slime Molds (SISMO) using case studies from the Carinthian region, demonstrating its applicability to various network structures. SISMO is inspired by the ability of the myxomycete Physarum polycephalum to process information and solve optimization tasks. The effectiveness of SISMO in network formation and finding shortest paths is first evaluated using parts of Carinthia’s bus and railway infrastructure. Our results show that SISMO can create networks similar to the existing transportation network, consider obstacles, and replicate existing connections. These findings allow conclusions for the future optimization of further networks using bio-inspired approaches. Based on these insights, this paper presents an approach that uses SISMO to create a repair plan for the Carinthian power transmission network after a simulated electromagnetic pulse attack. The algorithm is applied to a corresponding graph model to identify the most critical areas to be repaired, analogous to the nutrient supply of the slime mold between food sources. SISMO was adapted for this grid planning task and fed with the positions of relevant power plants and substations of the Carinthian electricity transmission grid. This approach has significant potential for diverse applications, especially those where the algorithms are not limited by the physical or infrastructural constraints that shaped the original network topology. Further exploration of this approach could yield significant insights into various fields. Overall, the paper provides insights into the potential applications of bio-inspired algorithms, such as slime mold simulation, for solving network planning tasks and presents concrete case studies from the Carinthian region.