The supply-demand optimization (SDO) algorithm is a new meta-heuristic optimization algorithm proposed by Zhao et al. in 2019 inspired by the economic supply and demand mechanism. The algorithm mathematically simulates the demand relationship of consumers and the supply relationship of producers. By introducing the stable mode and the unstable mode of the supply and demand mechanism into the SDO algorithm, the two modes are used to perform local search and global search in a given space. Search for solutions to optimization problems. Compared with the traditional swarm intelligence algorithm, the SDO algorithm has fast convergence speed, high optimization precision, fewer adjustment parameters, and better exploration and development capabilities. Please refer to this document for the principle of the code.
References: Cui Dongwen, Li Daihua. Improved supply and demand optimization algorithm for foundation pit deformation prediction-exponential power product model[J]. Water Conservancy and Hydropower Science and Technology Progress, 2020,40(04):43-50.
The CEC2005 test set is the most widely used and classic test set, including 23 Benchmark functions. The specific information is as follows:
Randomly select several functions, the algorithm iterates 500 times, and the resulting code is shown in the figure:
After testing the unimodal and multimodal functions, it can be seen that the performance of the supply and demand optimization SDO algorithm is still very good, and the optimization values are basically not much different from the theoretical values.
How to get the code, the key words of the card below: TGDM1209
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