Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches

Wu, Jui-Yu

doi:10.1155/2012/841410

Cited by 9 publications

(8 citation statements)

References 28 publications

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“…The PSO technique can be applied to power system problems such as reactive power and voltage control, economic dispatch, power system reliability and security, generation expansion problem, state estimation, load flow and optimal power flow, short-term load forecasting, and capacitor placement. Wu [11] proposed a hybrid real-coded genetic algorithm with a PSO algorithm and a hybrid artificial immune algorithm with a PSO algorithm to solve global optimization problems with 13 constraints. Kao et al [12] proposed a new hybrid algorithm based on two main swarm intelligence approaches, the ant colony optimization (ACO) and the PSO to solve capacitated vehiclerouting combinatorial optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Applying Hybrid PSO to Optimize Directional Overcurrent Relay Coordination in Variable Network Topologies

Yang

Liu

2013

Journal of Applied Mathematics

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In power systems, determining the values of time dial setting (TDS) and the plug setting (PS) for directional overcurrent relays (DOCRs) is an extremely constrained optimization problem that has been previously described and solved as a nonlinear programming problem. Optimization coordination problems of near-end faults and far-end faults occurring simultaneously in circuits with various topologies, including fixed and variable network topologies, are considered in this study. The aim of this study was to apply the Nelder-Mead (NM) simplex search method and particle swarm optimization (PSO) to solve this optimization problem. The proposed NM-PSO method has the advantage of NM algorithm, with a quicker movement toward optimal solution, as well as the advantage of PSO algorithm in the ability to obtain globally optimal solution. Neither a conventional PSO nor the proposed NM-PSO method is capable of dealing with constrained optimization problems. Therefore, we use the gradient-based repair method embedded in a conventional PSO and the proposed NM-PSO. This study used an IEEE 8-bus test system as a case study to compare the convergence performance of the proposed NM-PSO method and a conventional PSO approach. The results demonstrate that a robust and optimal solution can be obtained efficiently by implementing the proposal.

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Section: Introductionmentioning

confidence: 99%

Applying Hybrid PSO to Optimize Directional Overcurrent Relay Coordination in Variable Network Topologies

Yang

Liu

2013

Journal of Applied Mathematics

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“…Consistent with the Ab-Ag affinity metaphor, an Ab-Ag affinity is determined using (16) Step 3 is divided into two subsets. These Abs undergo somatic hypermutation operation by using (13) when the random number is 0.5 or less.…”

Section: Endmentioning

confidence: 99%

Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

2013

Mathematical Problems in Engineering

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Stochastic global optimization (SGO) algorithms such as the particle swarm optimization (PSO) approach have become popular for solving unconstrained global optimization (UGO) problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO) method and an artificial immune algorithm-based PSO (AIA-PSO) method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

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“…Finally, the optimal solutions obtained by the aforesaid methods were validated by a confirmation experiment to find out the optimum parameter combination. [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] The higher the thrust of the solder ball, the better it is, and therefore, it exhibits an LTB characteristic 25 SN LTB = À 10log 10 MSD ð Þ = À 10log 10 1 n…”

Section: Introductionmentioning

confidence: 99%

Using improved simulated anneal arithmetic to improve semiconductor packaging ball placement process capability

Wang

2018

Advances in Mechanical Engineering

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This study used improved simulated annealing arithmetic to improve the semiconductor packaging ball placement process capability. The simulated annealing computing process was combined with an artificial neural network, Metropolis algorithm, and sequential Gaussian simulation. Grey relation analysis was used as the target value, which is intended to obtain the optimum parameter design of process capability. The results showed that the substrate design-Pad Open is 0.30 mm ball size, 0.275 mm Pad open, Profile type B, maximum temperature 236 (°C), solder melting time 53 (s), preheating temperature 176 (°C), and a solder ball component, as SAC405 can result in a parameter design for optimal solder ball shear strength of C pk = 2.38 and G 0i = 0:87. This optimum parameter design process is better than other methods, and it reduces the cost waste of extra defectives.

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Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches

Cited by 9 publications

References 28 publications

Applying Hybrid PSO to Optimize Directional Overcurrent Relay Coordination in Variable Network Topologies

Applying Hybrid PSO to Optimize Directional Overcurrent Relay Coordination in Variable Network Topologies

Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

Using improved simulated anneal arithmetic to improve semiconductor packaging ball placement process capability

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