HIERARCHICAL MULTI-OBJECTIVE DECISION SYSTEMS AND POWER-DECENTRALIZED SYSTEMS FOR GENERAL RESOURCE ALLOCATION PROBLEMS.

This paper considers optimization methods for hierarchical power-decentralized systems composed of a coordinating central system and plural semi-autonomous local systems in the lower-level, each of which possesses a decision-making unit. Such a decentralized system where both central and local systems possess their own objective function and decision variables is hence a multi-objective system. The central system allocates resources so as to optimize its own objective, while the local ones optimize their own objectives using the given resources. The lower-level composes a multi-objective programming problem, where local decision-makers minimize a vector objective function in cooperation. Thus, the lower level generates a set of noninferior solutions being parametric w. r. t. the given resources. The central decision-maker, then, chooses an optimal resource allocation and the best corresponding noninferior solution from among a set of resource-parametric noninferior solutions.