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Fig. 1.
Schematic diagram of a supply network showing all possible relationships between the
participants
This paper presents a novel approach for self-structuring multiagent systems. Sec-
tion 2 further explores the challenges in logistics network configuration and operation.
Section 3 examines agent coordination mechanisms for organizing decentralized be-
havior in logistics networks. Motivated by these considerations, Section 4 introduces
expectation-based self-organization
as an adaptive structuring paradigm for multiagent
systems based on sociological theory. That approach is evaluated in Section 5 in a sim-
ulated supply network scenario with regard to coordination effort and logistics perfor-
mance. Finally, Section 6 recapitulates the achievements of this paper in a concluding
summary and gives an outlook on possible future work.
2
Self-Organizing Supply Networks
In order to efficiently solve repeatedly occurring coordination problems in decentralized
systems, organizational structures have to be established [8]. Yet, it is unclear which
kind of structure is applied best, given a particular coordination problem. Consider, for
instance, a logistics network as depicted in Figure 1. In this network, the participants
must choose which subset of the possible relationships between each two tiers (shown
as arrows in the direction of material flows) actually to establish. This decision has to
consider transaction costs (e.g., interaction effort and transportation costs) as well as the
responsiveness and reliability of possible business partners in order to enable efficient
operations within the network.
A supply network can be represented as a graph consisting of logistics entities as its
nodes and their possible business relationships as edges. Establishing an organizational
structure refers to the choice of a subgraph restricting the set of edges to a subset of
all possible ones. An efficient organizational structure furthermore minimizes the actu-
ally instantiated relationships while maximizing the achieved operations outcome with
regard to logistics performance measures.
However, due to the dynamics of logistics processes, conventional design time eval-
uation and optimization of these organizational structures is not sufficient in terms of
