Efficient Sampling When Searching for Robust Solutions

2016 ◽  
pp. 237-246 ◽  
Author(s):  
Juergen Branke ◽  
Xin Fei
Keyword(s):  
Robust Solutions ◽  
Efficient Sampling

The Rise of Partnerships: From Local to Global

2018 ◽  
Author(s):  
Barbara Gray ◽  
Jill Purdy
Keyword(s):  
Nongovernmental Organizations ◽  
Public Services ◽  
Civic Society ◽  
Robust Solutions ◽  
Essential Components ◽  
Critical Issues ◽  
Definition Of ◽  
Societal Problems ◽  
Shared Norms ◽  
Multistakeholder Partnerships

Multistakeholder partnerships (MSPs) are formed to tackle knotty societal problems, promote innovation, provide public services, expand governance capabilities, set standards for a field, or resolve conflicts that impede progress on critical issues. Partnerships are viewed as collaboration among four types of stakeholders: businesses, governments, nongovernmental organizations (NGOs), and civic society. The objective of collaboration is to create a richer, more comprehensive appreciation of the iss/problem than any of the partners could construct alone by viewing it from the perspectives of all the stakeholders and designing robust solutions. Such partnerships are necessary because few organizations contain sufficient knowledge and resources to fully analyze issues and take action on them unilaterally. Five essential components of a rigorous definition of collaboration are presented: interdependence among partners, emergence of shared norms, wrestling with differences, respect for different competencies, and assuming joint responsibility for outcomes. Several examples of MSPs are provided.

scholarly journals Identification of Efficient Sampling Techniques for Probabilistic Voltage Stability Analysis of Renewable-Rich Power Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2328
Author(s):  
Mohammed Alzubaidi ◽  
Kazi N. Hasan ◽  
Lasantha Meegahapola ◽  
Mir Toufikur Rahman
Keyword(s):  
Monte Carlo ◽  
Stability Analysis ◽  
Power Systems ◽  
Large Scale ◽  
Voltage Stability ◽  
Sampling Technique ◽  
Coefficient Of Determination ◽  
Sampling Techniques ◽  
Quasi Monte Carlo ◽  
Efficient Sampling

This paper presents a comparative analysis of six sampling techniques to identify an efficient and accurate sampling technique to be applied to probabilistic voltage stability assessment in large-scale power systems. In this study, six different sampling techniques are investigated and compared to each other in terms of their accuracy and efficiency, including Monte Carlo (MC), three versions of Quasi-Monte Carlo (QMC), i.e., Sobol, Halton, and Latin Hypercube, Markov Chain MC (MCMC), and importance sampling (IS) technique, to evaluate their suitability for application with probabilistic voltage stability analysis in large-scale uncertain power systems. The coefficient of determination (R2) and root mean square error (RMSE) are calculated to measure the accuracy and the efficiency of the sampling techniques compared to each other. All the six sampling techniques provide more than 99% accuracy by producing a large number of wind speed random samples (8760 samples). In terms of efficiency, on the other hand, the three versions of QMC are the most efficient sampling techniques, providing more than 96% accuracy with only a small number of generated samples (150 samples) compared to other techniques.

scholarly journals Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings

2013 ◽  
Vol 44 (2) ◽  
pp. 131-156 ◽  
Author(s):  
Laura Climent ◽  
Richard J. Wallace ◽  
Miguel A. Salido ◽  
Federico Barber
Keyword(s):  
Constraint Satisfaction ◽  
Constraint Satisfaction Problems ◽  
Robust Solutions
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