Topic B.1: Modeling of selected logistic networks for renewable resources from by-products and cascade utilization, taking uncertainties and risk management into consideration

In logistics, functioning networks are essential for the availability of products, but are becoming larger and often more complex and more dynamic due to increasing requirements, organizational forms, and the use of modern information and communication technology (Buchholz, Clausen, 2009). Operations Research knows many approaches to logistics, and recently planning schemes have specifically been developed in the field of reverse logistics (redistribution logistics) (Dekker et al., 2004). The development of tailor-made methods for the logistical planning of renewable resources is still in its infancy (Geldermann, Uhlemair, 2007; Uhlemair et al., 2010). The substitution of conventional materials by means of renewable resources from the production of by-products and cascade utilization specifically demands innovative resolutions. The assessment of logistical concepts’ resource efficiency represents a research gap due to the inherent uncertainties regarding the quantities available and the quality of the partial seasonal accrual of resources, as well as the frequently reduced storage life (e.g., decomposition and moisture loss).

Consequently, quantitative methods from logistics can be tested and further developed regarding their applicability to renewable resources (by-products and cascade utilization). The objective is conceiving and implementing a decision support system that determines the economically optimal solution based on the amount of raw material, its industrial applicability (topics A.2, A.3 and A.4), its possibility to generate energy (topic A.7), and the transport routes (between the raw material and their utilization locations, e.g., biorefineries and pellet heating). Methods are developed to determine economically useful logistics concepts, taking into account the transportation distance, maximum period of storage, and minimization of carbon dioxide emission. By means of the implemented model, scenarios are determined (e.g., firstly for MDF boards) and sensitivity analyses are carried out. Tests have to ascertain whether the parametric optimization is suitable to determine allowable parameter variations for the extent of the present problem.

Risk management is an essential component of logistical planning. The risks to be considered are firstly identified in conjunction with topic A.1. In addition to the magnitude of seasonal fluctuations, potential calamities - such as total loss due to natural disasters such as floods and storms - also have to be taken into account in the long-term planning. Approaches to estimate the economic risk and determine the extent of the required precautionary measures regarding renewable resources are tested for their suitability. The preliminary work in the field of risk management regarding natural disasters and industrial accidents (Geldermann et al., 2008; Bertsch, Geldermann, 2010) can be used as the basis.