Parallelization method of artificial immune optimization model for spatial layout of land utilization
A technology of artificial immunity and optimization model, applied in data processing application, prediction, calculation and other directions, can solve problems such as low efficiency
Active Publication Date: 2013-12-11
WUHAN UNIV
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[0024] Aiming at the inefficiency of the existing land use spatial layout parallel intelligent optimization technology in actual operation, a scalable, high parallel efficiency parallel multi-objective artificial immune intelligent optimization model is invented in a shared storage parallel environment
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[0042] Shared storage mainly includes computers with multi-core and multi-CPU personal computers and small workstations, which are distinguished from distributed storage computers. On a computer with a shared storage environment, the calculation data does not need to be transmitted through the network, thus reducing the time overhead caused by network transmission and having a greater potential for parallelism. The invention provides a parallelization method of the artificial immune optimization model of the land use space layout aiming at the shared storage environment. The technical solutions of the present invention will be described below in conjunction with the accompanying drawings and embodiments.
[0043] For ease of understanding, the theoretical basis is first explained:
[0044] Algorithms are usually parallelized in two ways: data parallelism and task parallelism. For the multi-target artificial immune system, because it takes the population composed of antibodie...
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The invention relates to a parallelization method of an artificial immune optimization model for spatial layout of land utilization. The parallelization method comprises the following steps of: resolving a multi-target artificial immune model focused on the optimization of the spatial layout of the land utilization, wherein a resolving result comprises a population initializing operator, a target vector computing operator, a selection operator, a clone operator, a mutation operator, a population updating operator and a decoding operator; constructing an immune operator array, sequentially storing the operators to be iteratively executed into the immune operator array, wherein the operators to be iteratively executed comprise the clone operator, the mutation operator, the target vector computing operator, the selection operator and the population updating operator; executing the population initializing operator and the target vector computing operator in parallel, and carrying out serial execution on the selection operator; respectively carrying out the parallel execution on the iteratively executed immune operator array, the clone operator, the mutation operator and the target vector computing operator, and sequentially carrying out the serial execution on the selection operator and the population initializing operator; finally carrying out the parallel execution on the decoding operator.
Description
technical field [0001] The invention belongs to the technical field of land use spatial layout optimization configuration, and in particular relates to a parallelization method of an artificial immune optimization model of land use space layout. Background technique [0002] Regarding the optimal allocation of land use spatial layout, there have been some achievements, mainly including the modeling of land resource spatial layout optimization and the combined application of multi-objective artificial immune system optimization technology. A brief introduction is as follows: [0003] 1. Modeling of the optimization problem of spatial layout of land resources [0004] The spatial layout optimization of land resources is an important part of land use planning. Its essence is to scientifically and rationally allocate various types of land in accordance with the natural and socio-economic characteristics of regional land resources under the constraints of the quantity structure ...
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IPC IPC(8): G06Q10/04
Inventor 刘耀林赵翔刘艳芳刘殿锋何建华焦利民
Owner WUHAN UNIV