• No results found

A hybrid particle swarm evolutionary algorithm for constrained multi-objective optimization

N/A
N/A
Protected

Academic year: 2019

Share "A hybrid particle swarm evolutionary algorithm for constrained multi-objective optimization"

Copied!
18
0
0

Loading.... (view fulltext now)

Full text

Loading

Figure

Fig. 1. Crowding distance calculation
Fig. 2. The total force imposed on y
Table 1. Parameter settings in F2 ∼ F4
Fig. 3. Statistical performance on F1
+5

References

Related documents

W ith a tradition of over 30 years counseling REITs, Shaw Pittman’s REIT practice of real estate, corporate, securities, and tax lawyers advises public and private REITs nationally

Cu(II), Zn(II) exhibit tetragonal structure were as Mo(II) and Fe(II) complexes exhibit octahedral structure.. The proposed structure of Cu (II), Zn (II), Mo (II) and Fe (II)

Transformation plans for children and young people’s mental health provision 1–3 focus on early identification, increasing access to services and reducing waiting times for

For this purpose, first, a one-dimensional aerodynamic flow-model is devel- oped, and used to evaluate the effect of blade-specific sur- face roughness on the performance of

In this narrative review, we highlighted that there is some evidence that exogenous melatonin may alter pubertal timing in some animals, that photoperiodic and melatonin

In fact, targeted ob- servations have to go through the assimilation scheme, to- gether with conventional data, to produce initial conditions, and their efficiency is strongly

Considering the surfeit of pitfalls associated with the lack of transparency in nonprofit organizations, and the apparent number of boards of national

Sire ID: ID number of the male parent of the specimen (For Zoo specimens only) Format: alphanumerical.