Open Access
Issue |
RAIRO-Oper. Res.
Volume 57, Number 6, November-December 2023
|
|
---|---|---|
Page(s) | 3033 - 3060 | |
DOI | https://doi.org/10.1051/ro/2023158 | |
Published online | 30 November 2023 |
- S. Baillargeon and L. Rivest, A general algorithm for univariate stratification. Int. Stat. Rev. 77 (2009) 331–344. [CrossRef] [Google Scholar]
- S. Baillargeon and L. Rivest, The construction of stratified designs in R with the package stratification. Surv. Methodol. 37 (2011) 53–65. [Google Scholar]
- M. Ballin and G. Barcarolli, Joint determination of optimal stratification and sample allocation using genetic algorithm. Surv. Methodol. 39 (2013) 369–393. [Google Scholar]
- M. Bankier, Power allocation: determining sample sizes for subnational areas. Am. Stat. 42 (1988) 174–177. [Google Scholar]
- C. Blum, J. Puchinger, G.R. Raidl and A. Roli, Hybrid metaheuristics in combinatorial optimization: a survey. Appl. Soft Comput. 11 (2011) 4135–4151. [CrossRef] [Google Scholar]
- R. Bouabda, B. Jarboui, M. Eddaly and A. Rebaï, A branch and bound enhanced genetic algorithm for scheduling a flowline manufacturing cell with sequence dependent family setup times. Comput. Oper. Res. 38 (2011) 387–393. [CrossRef] [Google Scholar]
- J. Brito, N. Maculan, M. Lila and F. Montenegro, An iterative local search approach applied to the optimal stratification problem. Int. Trans. Oper. Res. 17 (2010) 753–764. [CrossRef] [MathSciNet] [Google Scholar]
- J. Brito, N. Maculan, M. Lila and F. Montenegro, An exact algorithm for the stratification problem with proportional allocation. Optim. Lett. 4 (2015) 185–195. [Google Scholar]
- J. Brito, P. Silva, G. Semaan and N. Maculan, Integer programming formulations applied to optimal allocation in stratified sampling. Surv. Methodol. 41 (2015) 427–442. [Google Scholar]
- J. Brito, G. Semaan, A. Fadel and L. Brito, An optimization approach applied to the optimal stratification problem. Commun. Stat. Simul. Comput. 46 (2017) 4419–4451. [CrossRef] [Google Scholar]
- J. Brito, T. Veiga and P. Silva, An optimisation algorithm applied to the one-dimensional stratification problem. Surv. Methodol. 45 (2019) 295–315. [Google Scholar]
- J. Brito, L. de Lima, P. Gonzalez, B. Oliveira and N. Maculan, Heuristic approach applied to the optimum stratification problem. RAIRO: Oper. Res. 55 (2021) 979–996. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
- J.A. Brito, G. Semaan, L. de Lima and A. Fadel, Algorithm for univariate stratification problem. https://github.com/jambrito/STRATMH (2023). [Google Scholar]
- W. Cochran, Sampling Techniques, 3rd edition. John Wiley, New York (1977). [Google Scholar]
- E. Creaco and G. Pezzinga, Embedding linear programming in multi objective genetic algorithms for reducing the size of the search space with application to leakage minimization in water distribution networks. Environ. Modell. Softw. 69 (2015) 308–318. [CrossRef] [Google Scholar]
- T. Dalenius and J.J. Hodges, Minimum variance stratification. J. Am. Stat. Assoc. 54 (1959) 88–101. [CrossRef] [Google Scholar]
- F. Danish, A mathematical programming approach for obtaining optimum strata boundaries using two auxiliary variables under proportional allocation. Stat. Transition New Ser. 19 (2018) 507–526. [CrossRef] [Google Scholar]
- F. Danish and S. Rizvi, Optimum stratification in Bivariate auxiliary variables under Neyman allocation. J. Mod. Appl. Stat. Methods 17 (2018) 2–24. [CrossRef] [Google Scholar]
- F. Danish, S. Rivsi, M. Sharma and M. Jeelani, Optimum stratification using mathematical programming approach: a review. J. Stat. App. Probab. Lett. 4 (2017) 123–129. [CrossRef] [Google Scholar]
- F. Danish, S. Rizvi, M. Sharma, M.I. Jeelani, B. Kumar and Q. Da Farooq, Optimum stratification for two stratifying variables. Revista Investigacion Operacional 40 (2019) 562–573. [Google Scholar]
- F.M. Defersha and S. Bayat Movahed, Linear programming assisted (not embedded) genetic algorithm for flexible jobshop scheduling with lot streaming. Comput. Ind. Eng. 117 (2018) 319–335. [CrossRef] [Google Scholar]
- G. Ekman, An approximation useful inf univariate stratification. Ann. Math. Stat. 30 (1959) 219–229. [CrossRef] [Google Scholar]
- A. Fadel, L. Ochi, J.A.M. Brito and G. Semaan, Microaggregation heuristic applied to statistical disclosure control. Inf. Sci. 548 (2021) 37–55. [CrossRef] [Google Scholar]
- P. Festa, A biased random-key genetic algorithm for data clustering. BIOCOMP Math. Biosci. 245 (2013) 76–85. [CrossRef] [Google Scholar]
- J.F. Gonçalves and M.G. Resende, Biased random-key genetic algorithms for combinatorial optimization. J. Heuristics 17 (2013) 487–525. [Google Scholar]
- J.F. Gonçalves and M.G. Resende, A biased random-key genetic algorithm for the unequal area facility layout problem. Eur. J. Oper. Res. 246 (2015) 86–107. [CrossRef] [Google Scholar]
- P. Gunning and J. Horgan, A new algorithm for the construction of stratum boundaries in skewed populations. Surv. Methodol. 30 (2004) 159–166. [Google Scholar]
- D. Hedlin, A procedure for stratification by an extended Ekman rule. J. Official Stat. 16 (2000) 15–29. [Google Scholar]
- M. Hidiroglou and M. Kozak, Stratification of skewed populations: a comparison of optimisation-based versus approximate methods. Int. Stat. Rev. 86 (2018) 87–105. [Google Scholar]
- T. Keskintürk and S. Er, A genetic algorithm approach to determine stratum boundaries and sample sizes of each stratum in stratified sampling. Comput. Stat. Data Anal. 52 (2007) 53–67. [Google Scholar]
- E. Khan, M. Khan and M. Ahsan, Optimum stratification: a mathematical programming approach. Calcutta Stat. Assoc. Bull. 52 (2002) 323–334. [CrossRef] [Google Scholar]
- M. Khan, N. Nand and N. Ahmad, Determining the optimum strata boundary points using dynamic programming. Surv. Methodol. 34 (2008) 205–214. [Google Scholar]
- M. Khan, D. Rao, A. Ansari and M. Ahsan, Determining optimum strata boundaries and sample sizes for skewed population using log-normal distribution. Commun. Stat. Simul. Comput. 44 (2015) 1364–1387. [CrossRef] [MathSciNet] [Google Scholar]
- M. Khan, K. Reddy and D. Rao, Designing stratified sampling in economic and business surveys. J. Appl. Stat. 42 (2015) 2080–2099. [CrossRef] [MathSciNet] [Google Scholar]
- M. Kozak, Optimal stratification using random search method in agricultural surveys. Stat. Transition 6 (2004) 797–806. [Google Scholar]
- M. Kozak, Comparison of random search method and genetic algorithm for stratification. Commun. Stat. Simul. Comput. 43 (2014) 249–253. [Google Scholar]
- M. Kozak and M. Verma, Geometric versus optimization approach to stratification: a comparison of efficiency. Surv. Methodol. 32 (2006) 157–163. [Google Scholar]
- P. Lavallée and M. Hidiroglou, On the stratification of skewed populations. Surv. Methodol. 14 (1988) 33–43. [Google Scholar]
- J. Lisic, H. Sang, Z. Zhu and S. Zimmer, Optimal stratification and allocation for the june agricultural survey. J. Official Stat. 34 (2018) 121–148. [Google Scholar]
- S. Lohr, Sampling: Design and Analysis, 2nd edition. Chapman & Hall (2019). [CrossRef] [Google Scholar]
- R. Mart, P. Pardalos and M. Resende, Handbook of Heuristics, 1st edition. Springer (2018). [CrossRef] [Google Scholar]
- K. Reddy and M. Khan, Optimal stratification in stratified designs using weibull-distributed auxiliary information. Commun. Stat. Theory Methods 48 (2019) 3136–3152. [Google Scholar]
- K. Reddy and M. Khan, stratifyR: an R package for optimal stratification and sample allocation for univariate populations. Aust. New Zealand J. Stat. 62 (2020) 383–405. [Google Scholar]
- M. Reisi-Nafchi and G. Moslehi, A hybrid genetic and linear programming algorithm for two-agent order acceptance and scheduling problem. Appl. Soft Comput. 33 (2015) 37–47. [CrossRef] [Google Scholar]
- L. Rivest, A generalization of the Lavallée and Hidiroglou algorithm for stratification in business surveys. Surv. Methodol. 28 (2020) 191–198. [Google Scholar]
- G. Semaan, J.A.M. Brito, I. Coelho, E.F. Silva, A. Fadel, L.S.O. Ochi and N. Maculan, A brief history of heuristics: from bounded rationality to intractability. IEEE Latin Am. Trans. 18 (2020) 1975–1986. [CrossRef] [Google Scholar]
- V. Sethi, A note on the optimum stratification of populations for estimating the population means. Aust. New Zealand J. Stat. 5 (1963) 20–33. [Google Scholar]
- M. Triola, Elementary Statistics, 14th edition. Pearson (2021). [Google Scholar]
- V. Unnithan, The minimum variance boundary points of stratification. Sankhya 40 (1978) 60–72. [Google Scholar]
- Y. Xiao and A. Konak, A genetic algorithm with exact dynamic programming for the green vehicle routing & scheduling problem. J. Cleaner Prod. 167 (2017) 1450–1463. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.