An Approach For Multi-object Decision Making Based On Skyline Query

Decision is a process in which we can find a satisfy solution from all the feasible solutions. In reality, people will face the diversity of the target. Because of the diversity and complex of the target, it is difficult to find the "best" solution. The problem becomes complicated, but also interesting. MODM (multiple objective decision making) is a discipline aimed at making decisions in the multiple, often conflicting objectives. Recently, a lot of methods have been proposed. The most mature methods separately are Conventional mathematics methods which are aiming at converting multiple objectives to a single objective and the methods based on intelligent optimization. But the global optimality cannot be ensured in these methods.According to the disadvantages of traditional methods, we propose a new method named as SBASM which is based on Skyline Query. It is proposed on the basis of Posterior priority technology. SBASM which uses intrinsic parallel mechanism and full optimization to search for solutions of MODM overcame the shortcomings that exist in the original methods in which only one solution can be obtained once a time. Furthermore the SBASM successfully achieved the tradeoffs of different objectives.In order to facilitate the search, we need to preprocess the data, and then according to the quad-tree structural characteristics and the division of the regional inter-relations of domination, a new Skyline Query Algorithm-QBSQ is proposed. QBSQ can achieve all non-inferior solution and reduce the impact of decision maker’s preferences when acting on the pretreatment data. In order to help decision-makers choose the best solution as soon as possible, we put all the non-inferior solutions in the Skyline-Decision Tree which shows the relations between all the non-inferior solutions. Obviously, it is impossible to obtain high-precision point the first time. So we need to gradually increase the accuracy of the data using the C.M. Through these continuous processes, decision makers can make better decisions. At last, the simulation results prove the validity, correctness and feasibility of SBASM.