Coordinating Multiagent Industrial Symbiosis

In such networks, symbiosis leads to socioeconomic and environmental benefits for involved industrial agents and the society (see [14, 39]). One barrier against stable ISN implementations is the lack of frameworks able to secure such networks against unfair and unstable allocation of obtainable benefits among the involved industrial firms. In other words, although in general ISNs result in the reduction of the total cost, a remaining challenge for operationalization of ISNs is to tailor reasonable mechanisms for allocating the total obtainable cost reductions--in a fair and stable manner--among the contributing firms. Otherwise, even if economic benefits are foreseeable, lack of stability and/or fairness may lead to non-cooperative decisions. This will be the main focus of what we call the industrial symbiosis implementation problem. Reviewing recent contributions in the field of industrial symbiosis research, we encounter studies focusing on the necessity to consider interrelations between industrial enterprises [43, 47] and the role of contract settings in the process of ISN implementation [1, 44]. We believe that a missed element for shifting from theoretical ISN design to practical ISN implementation is to model, reason about, and support ISN decision processes in a dynamic way (and not by using snapshotbased modeling frameworks). For such a multiagent setting, the mature field of cooperative game theory provides rigorous methodologies and established solution concepts, e.g. the core of the game and the Shapley allocation [15, 30, 34, 7]. However, for ISNs modeled as a cooperative game, these established solution concepts may be either non-feasible (due to properties of the game, e.g.