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This paper proposes a modified particle swarm optimization algorithm for engineering optimization problems with constraints, in which the penalty function is employed to the traditional PSO algorithm, and at the same time adjusts the personal optimum and global optimum to make PSO being able to solve the non-linear programming problems, then the multi-objective problem can be converted into single...
In this paper, based on the bionic study on dolphin, a philosophy of dolphin Partner Optimization (DPO) was formulated and a so-called ldquoNucleusrdquo was introduced to predict the best position according to the positions and fitness of the team members. After that, we test the DPO algorithm on several benchmark functions and the experiment result show it has rapid and niche character and good adaptability...
This paper proposes a novel optimization algorithm called cellular probabilistic optimization algorithms (CPOA) based on the probabilistic representation of solutions for real coded problems. In place of binary integers, the basic unit of information here is a probability density function. This probabilistic coding allows superposition of states for a more efficient algorithm. This probabilistic representation...
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