Index and direction vector-combined multi-objective optimization method and system
A multi-objective optimization, direction vector technology, used in data processing applications, forecasting, instrumentation, etc.
Inactive Publication Date: 2017-09-01
SHENZHEN UNIV
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[0018] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a multi-objective optimization method and system based on the combination of indicators and direction vectors, aiming at solving the problem that the existing multi-objective optimization algorithm cannot simultaneously improve the convergence and Diversity issues
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[0082] The present invention provides a multi-objective optimization method and system based on the combination of indicators and direction vectors. In order to make the purpose, technical solutions and effects of the present invention clearer and clearer, the present invention will be further described in detail below. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0083] see figure 1 , figure 1 It is a flowchart of a preferred embodiment of the multi-objective optimization method based on the combination of indicators and direction vectors according to the present invention, such as figure 1 As shown, it includes the steps:
[0084] Step S100, initializing the direction vector, the evolutionary population, and the ideal point vector;
[0085] Step S200, generating new individuals according to the initialized evolutionary population;
[0086] Step S300, merge the ne...
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The invention discloses an index and direction vector-combined multi-objective optimization method and system. The method includes the following steps that: a direction vector, an evolutionary population and an ideal point vector are initialized; new individuals are generated according to the initialized evolutionary population; and the new individuals and the initialized evolutionary population are merged, so that non-dominated solutions in the merged evolutionary population are obtained, the merged evolutionary population is iterated until the number of the non-dominated solutions in the merged evolutionary population in equal to the size of the initialized evolutionary population, and solutions corresponding to the iterated evolutionary population are outputted. According to the method and system of the invention, the Pareto dominance relation can be replaced, the problem of selective pressure decrease caused by the large proportion of non dominated individuals can be effectively alleviated; dual epsilon indexes strictly accord with the consistency of the Pareto dominance, and the computational complexity of the method of the invention is relatively low compared to the indexes; and additional parameter settings are not needed, and therefore, calculation is simple.
Description
technical field [0001] The invention relates to the field of multi-objective optimization, in particular to a multi-objective optimization method and system based on the combination of indicators and direction vectors. Background technique [0002] When solving optimization problems in engineering practice and scientific research, if only one objective function is considered, it is called a single-objective optimization problem; Independence, that is, when an objective function is improved, the performance of other objective functions will be reduced to a certain extent. Such a situation is called a multi-objective optimization problem. The optimal solution of a single-objective optimization problem is usually a uniquely determined optimal solution, while the solution of a multi-objective optimization problem is usually a set of irreconcilable objective functions, which is usually called Pareto optimal solution or non-dominated solution. [0003] In life, we often face mul...
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IPC IPC(8): G06Q10/04G06N3/00
CPCG06N3/006G06Q10/04
Inventor 骆剑平杨芸
Owner SHENZHEN UNIV