Recently multi-objective optimization (MOP) that can support agile and flexible decision-making has been highly required to deal with complex and global decision environment. We have proposed, in this paper, a new method relying on a prior articulation in tradeoff analysis among conflicting objectives. To overcome stiffness and shortcomings of the conventional methods, a novel approach has been developed by the virtue of simple subjective judgment and neural networks. Then incorporating the value function thus identified into the optimization procedure, we have given a general framework for solving MOP. Since the value function is decided by simple and relative responses that will be done separately from the searching process, DM's tradeoff analysis is not only very easy but also of small load compared with the conventional interactive methods. Another advantage is that we can carry out MOP based on the method viewed most suitable under present consideration. Finally, an illustrative application will be provided to outline the proposed method and verify its effectiveness.