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Method for improving gravitation search algorithm by use of compound form method

A technology of gravity search algorithm and compound shape method, applied in the field of intelligent optimization algorithm, can solve problems such as weak local search ability, avoid premature convergence and improve optimization performance.

Inactive Publication Date: 2014-08-27
JIANGNAN UNIV
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Problems solved by technology

[0005] Aiming at the above problems, the present invention introduces the complex operator into the gravitational search algorithm to overcome the weak local search ability of the gravitational search algorithm, avoid premature convergence, and improve the optimization performance of the algorithm

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  • Method for improving gravitation search algorithm by use of compound form method
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  • Method for improving gravitation search algorithm by use of compound form method

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Embodiment Construction

[0014] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0015] A method for improving the gravitational search algorithm by using the compound shape method, the optimization steps are as follows:

[0016] Step 1: Set the number of populations as N, the dimension of space as D, and the maximum number of iterations as T, and randomly initialize the position of each particle in the population i=1, 2, . . . , N. in, Indicates the position of particle i in the d-dimensional space.

[0017] Step 2: According to the objective function, calculate the fitness value f of each particle i (t) (i=1, 2, . . . , N).

[0018] Step 3: Update the inertial mass of each particle in the population. According to formula (1) and formula (2), calculate the inertial mass M of each particle i (t):

[0019] m i ( t ) = ...

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Abstract

The invention relates to the intelligent optimization algorithm field and discloses a method for improving a gravitation search algorithm by use of a compound form method. The compound form method is used for enhancing the local search ability of the gravitation search algorithm: the gravitation search algorithm is used for global search to find the optimal particle position; two premature decision conditions are introduced, the population fitness variance sigma 2 of the current population is less than alpha and the average distance D(t) between particles is less than beta (alpha and beta are predetermined small thresholds); if the two conditions are satisfied, the premature convergence phenomenon of the gravitation search algorithm occurs and then the compound form method is introduced, and the optimal particle position found by the gravitation search algorithm at present is taken as an initial compound form vertex and local search is carried out by use of relatively powerful local search ability of the compound form method; a compound form vertex formed at last is taken as a new particle position value of the gravitation search algorithm to continue searching. The method for improving the gravitation search algorithm by use of the compound form method is capable of effectively avoiding the premature convergence phenomenon of the gravitation search algorithm, and therefore, the optimal performance of the algorithm is improved.

Description

technical field [0001] The invention relates to a method for improving a gravitational search algorithm by adopting a compound shape method, and belongs to the field of intelligent optimization algorithms. Background technique [0002] The gravitational search algorithm is a new meta-heuristic optimization algorithm based on Newton's law of universal gravitation proposed by Professor Esmat of Iran in 2009. Similar to the particle swarm optimization algorithm, the gravity search algorithm also solves the problem through the random search of swarm intelligence. In the gravitational search algorithm, all individuals are regarded as particles with mass. Particles with low mass will be attracted by particles with large mass due to gravitational force. Therefore, the population will continue to move towards the particles with large mass, and finally find the mass with the largest mass. The particle is the optimal solution of the optimization problem. The gravity search algorithm...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9032
Inventor 潘丰戴娟
Owner JIANGNAN UNIV
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