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In this paper, improved Logistic models are given, which are called Logarithm Logistic Models. Based on U.S. Census data, the parameters of the models were estimated by applying the Least Squares Method. The experiments show that the prediction value of the new models is much closer to the actual value than the classical Logistic model. Finally, through analyzing the rationality of the maximum population...
The Harmony Search (HS) method is an emerging meta-heuristic optimization algorithm. However, it is generally not so efficient in dealing with multi-modal optimization problems, in which instead of only a single optimum, multiple optima need to be found. In our paper, a novel HS method based on the niching technique (deterministic crowding), n-HS, is proposed and studied to overcome this shortcoming...
Constrained optimization problems (COPs) are converted into a bi-objective optimization problem first, and a novel fitness function based on achievement scalarizing function (ASF) is presented. The fitness function adopts the valuable properties of ASF and can measure the merits of individuals by the weighting distance from the ndividuals to the reference point, where the reference point and the weighting...
The unidirectional logistics distribution vehicle routing problem with no time windows is considered. It contains the vehicle capacity restriction, the longest distance restriction and the full loaded vehicle. The solution must ensure the non-full loaded factor is the least and the total distance is the shortest. A multi-objective optimization mathematical model for the problem is established. And...
A novel Cultural Quantum-behaved Particle Swarm Optimization algorithm (CQPSO) is proposed in this paper to improve the performance of the Quantum-behaved PSO (QPSO). The cultural framework is embedded in our QPSO, and the knowledge stored in the belief space can guide the evolution of the QPSO. A total of 15 high-dimensional and multi-modal functions as well as an optimal pressure vessel design problem...
The conventional resource allocation method is so-called two-step method in OFDM system. The two-step method can reduce the computational complexity. However, it's solution accuracy is not very good. This paper proposes an improved two-step method. This method combines evolutionary algorithm with simulated annealing thought, and can take into account the sub-carrier distribution and power distribution...
Evolutionary Multi-objective Optimization (EMO) approaches have been amply applied to find a representative set of Pareto-optimal solutions in the past decades. Although there are advantages of getting the range of each objective and the shape of the entire Pareto front for an adequate decision-making, the task of choosing a preferred set of Pareto-optimal solutions is also important. In this paper,...
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