Anwendung und Verbesserung von Algorithmen der Computational Intelligence zur Modellierung und Optimierung komplexer Probleme der Planung von Supply Chains und der Vorhersagen und Epidemien (CI-SC Epidemics)

Basic data for this project

Description

Planning the activities in a large supply and distribution network is a highly complex task involving a large number of actors, deciding about a multitude of parameters like production and transportation volumes or inventory levels. Current methods being applied are based on classical methods of operations research or different meta‐heuristics, resulting very often in not acceptable run times. Besides the sheer complexity of the planning task the involvement of independent actors requires methods of decentralized planning. From the computational side mainly agent‐based methods are being applied to cover this aspect. The same complexity is found in epidemiological modeling of viral disease outbreaks, as hidden relations among actors have to be understood for usable forecast to be produced. The project sets out to find novel approaches or these complex planning tasks by applying compuational intelligence techniques such as metahrustic optimization algorithms and agent-based social simulation. It is performed in cooperation with the Brazilian Universidade de Pernambuco and the Institute of Molecular Virology of the WWU Münster.