Moving towards an optimal sample using VNS algorithm

Priyaranjan DASH; Samrat HORE

Article Details

Moving towards an optimal sample using VNS algorithm

Authors:

Priyaranjan DASH | Samrat HORE

Publisher:

Hacettepe University

Main Topics:

Analysis

Journal:

Hacettepe Journal of Mathematics and Statistics 2016 Vol.45 Issue 5, pp.1519-1524

Document Type:

Article

Publication Date:

9/2016

Document Language:

English

Document ID (Org No.):

2000452486

Frequency:

Bimonthly

eISSN:

2651-477X

pISSN:

2651-477X

Abstract:

 

In almost all random sampling schemes, we adopt different sampling designs with an objective of obtaining a better representative sample (optimal sample) for the population. Application of different randomization techniques were adopted for providing a supportive basis for this. Now the question arises, whether the final sample selected, on which all our efforts are utilized, from the population is an optimal sample or not? No where we are checking about the optimality of this sample, i.e., whether this sample is the best one or there exists any other sample which is more optimal than the selected one satisfying all the constraints. In all these procedures, we only assume but, nowhere we are establishing a guarantee about the achievement of such a representative sample. The present paper emphasizes on achieving an optimal sample by using variable neighborhood search (VNS) technique. .

Article Details

Moving towards an optimal sample using VNS algorithm

Authors: Priyaranjan DASH | Samrat HORE

Publisher: Hacettepe University

Main Topics: Analysis

Journal: Hacettepe Journal of Mathematics and Statistics 2016 Vol.45 Issue 5, pp.1519-1524

Document Type: Article

Publication Date: 9/2016

Document Language: English

Document ID (Org No.): 2000452486

Frequency: Bimonthly

eISSN: 2651-477X

pISSN: 2651-477X

Issues

Authors:

Priyaranjan DASH | Samrat HORE

Publisher:

Hacettepe University

Main Topics:

Analysis

Journal:

Hacettepe Journal of Mathematics and Statistics 2016 Vol.45 Issue 5, pp.1519-1524

Document Type:

Article

Publication Date:

9/2016

Document Language:

English

Document ID (Org No.):

2000452486

Frequency:

Bimonthly

eISSN:

2651-477X

pISSN:

2651-477X