Decentralized planning for multiobjective resource allocation and project selection

Complex decision problems like the selection of R&D projects often involve several parties with different and sometimes conflicting objectives. Since it cannot be expected that the parties are able and willing to provide a complete specification of their preferences in the form of a utility function, several interactive methods for group decision making with multiple criteria have been proposed in the literature. Most of these approaches assume that the set of decision alternatives of group members is fixed. However, this no longer is valid when the decision also involves the allocation of shared resources. Resource allocation problems have been studied in the previous literature mostly in the context of hierarchical organizations, where a higher level decision maker takes the ultimate responsibility. The present paper considers multiobjective resource allocation problems in a decentralized setting between group members of equal rank, who seek to obtain a fair compromise. It thus combines the previous research on group decision making on one hand and resource allocation on the other hand. We propose an iterative approach to solve this problem, and use computational experiments to compare it to other approaches modeled after earlier theoretical work and practical planning procedures.