[1] Aida, K., Cooper, W.W., Pastor, J.T. and Sueyoshi, T. Evaluating wa-ter supply services in Japan with RAM: a range-adjusted measure of inefficiency, Omega, 26(2) (1998), 207–232.
[2] Alirezaee, M., Hajinezhad, E. and Paradi, J.C. Objective identification of technological returns to scale for data envelopment analysis models, Eur. J. Oper. Res. 266(2) (2018), 678–688.
[3] Allen, R., Athanassopoulos, A., Dyson, R.G. and Thanassoulis, E. Weights restrictions and value judgements in data envelopment anal-ysis: evolution, development and future directions, Ann. Oper. Res. 73 (1997), 13–34.
[4] Arcelus, F.J., Sharma, B. and Srinivasan, G. The Human Development Index Adjusted for Efficient Resource Utilization, in Inequality, Poverty and Well-being, M. McGillivray, Editor., Palgrave Macmillan UK: Lon-don, 2006, 177–193.
[5] Banker, R.D., Charnes, A. and Cooper, W.W. Some models for esti-mating technical and scale ineffciencies in data envelopment analysis, Manag. Sci. 30(9) (1984), 1078–1092.
[6] Bard, J.F. and Falk, J.E. An explicit solution to the multi-level program-ming problem, Comput. Oper. Res. 9(1) (1982) 77–100.
[7] Bilbao-Ubillos, J. Another Approach to Measuring Human Development: The Composite Dynamic Human Development Index, Soc. Indic. Res. 111(2) (2013), 473–484.
[8] Blancard, S. and Hoarau, J.F. Optimizing the formulation of the united nations’ human development index: an empirical view from data envel-opment analysis, Econ. Bull. 31(1) (2011) 989–1003.
[9] Blancard, S. and Hoarau, J.F. A new sustainable human development indicator for small island developing states: A reappraisal from data envelopment analysis, Econ. Model. 30 (2013) 623–635.
[10] Bougnol, M.L., Dulá, J.H., Lins, M.E. and Da Silva, A.M. Enhancing standard performance practices with DEA, Omega, 38(1-2) (2010) 33–45.
[11] Boussofiane, A., Dyson, R.G. and Thanassoulis, E. Applied data envel-opment analysis, Eur. J. Oper. Res. 52(1) (1991), 1–15.
[12] Bracken, J. and McGill, J. Mathematical programs with optimization problems in the constraints, Oper. Res. 21 (1973), 37–44.
[13] Camanho, A.S. and D’Inverno, G. Data Envelopment Analysis: A Re-view and Synthesis, In: Macedo, P., Moutinho, V., Madaleno, M. (eds), Advanced Mathematical Methods for Economic Efficiency Analysis, Lec-ture Notes in Economics and Mathematical Systems, vol 692, Springer, Cham, 2023.
[14] Candler, W. and Norton, R.D. Multi-level programmin, World Bank, 20, 1977.
[15] Chansarn, S. The evaluation of the sustainable human development: A cross-country analysis employing slack-based DEA, Procedia. Environ. Sci. 20 (2014) 3–11.
[16] Charnes, A., Cooper, W.W., Golany, B., Seiford, L. and Stutz, J. Foun-dations of data envelopment analysis for Pareto-Koopmans efficient em-pirical production functions, J. Econom. 30(1-2) (1985) 91–107.
[17] Charnes, A., Cooper, W.W. and Rhodes, E. Measuring the efficiency of decision making unit, Eur. J. Oper. Res. 2 (1978) 429–444.
[18] Charnes, A., Cooper, W.W., Seiford, L. and Stutz, J. A multiplicative model for efficiency analysis, Socio-Econ. Plan. Sci. 16(5) (1982) 223–224.
[19] Charnes, A., Cooper, W.W., Seiford, L. and Stutz, J. Invariant mul-tiplicative efficiency and piecewise Cobb-Douglas envelopments, Oper. Res. Lett. 2(3) (1983) 101–103.
[20] Charnes, A., Cooper, W.W., Wei, Q.L. and Huang, Z.M. Cone ratio data envelopment analysis and multi-objective programming, Int. J. Syst. Sci. 20(7) (1989) 1099–1118.
[21] Cherchye, L., Moesen, W., Rogge, N. and Puyenbroeck, T.V. An in-troduction to ‘benefit of the doubt’composite indicators, Soc. Indic. Res. 82(1) (2007) 111–145.
[22] Colson, B., Marcotte, P. and Savard, G. Bilevel programming: A survey, 4or, 3(2) (2005), 87–107.
[23] Cook, W.D. and Seiford, L.M. Data envelopment analysis (DEA) –Thirty years on, Eur. J. Oper. Res. 192(1) (2009) 1–17.
[24] Cook, W.D., Tone, K. and Zhu, J. Data envelopment analysis: Prior to choosing a model, Omega, 44 (2014), 1–4.
[25] Cooper, W.W., Seiford, L.M., Tone, K. and Zhu, J. Some models and measures for evaluating performances with DEA: past accomplishments and future prospects, J. Product. Anal. 28(3) (2007)151–163.
[26] Deb, K. and Sinha, A. Solving bilevel multi-objective optimization prob-lems using evolutionary algorithms, in International conference on evo-lutionary multi-criterion optimization, Springer, 2009.
[27] Despotis, D.K. A Reassessment of the human development index via data envelopment analysis, J. Oper. Res. Soc. 56(8) (2005), 969–980.
[28] Despotis, D.K. Measuring human development via data envelopment analysis: the case of Asia and the Pacific, Omega, 33(5) (2005), 385–390.
[29] Dyson, R.G., Allen, R., Camanho, A.S., Podinovski, V.V., Sarrico, C.S. and Shale, E.A. Pitfalls and protocols in DEA, Eur. J. Oper. Res. 132(2) (2001) 245–259.
[30] Dyson, R.G. and Thanassoulis, E. Reducing weight flexibility in data envelopment analysis, J. Oper. Res. Soc. 39(6) (1988) 563–576.
[31] Edirisinghe, N.C.P. and Zhang, X. Generalized DEA model of funda-mental analysis and its application to portfolio optimization, J. Bank. Finance. 31(11) (2007), 3311–3335.
[32] Emrouznejad, A., Parker, B.R. and Tavares, G. Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA, Socio-Econ. Plan. Sci. 42(3) (2008), 151–157.
[33] Emrouznejad, A., Yang, Gl., Khoveyni, M. and Michali, M. Data En-velopment Analysis: Recent Developments and Challenges, In: Salhi, S., Boylan, J. (eds), The Palgrave Handbook of Operations Research (2022) 307–350.
[34] Farrell, M.J. The measurement of productive efficiency, J. R. Stat. Soc. 120(3) (1957) 253–281.
[35] Fethi, M.D. and Pasiouras, F. Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey, Eur. J. Oper. Res. 204(2) (2010) 189–198.
[36] Gattoufi, S., Oral, M., Kumar, A. and Reisman, A. Epistemology of data envelopment analysis and comparison with other fields of OR/MS for relevance to applications, Socio-Econ. Plan. Sci. 38(2-3) (2004) 123–140.
[37] Gattoufi, S., Oral, M. and Reisman, A. Data envelopment analysis lit-erature: a bibliography update (1951–2001), Socio-Econ. Plan. Sci. 38 (2004), 159–229.
[38] Golany, B. and Roll, Y. An application procedure for DEA, Omega, 17(3) (1989), 237–250.
[39] Hashimoto, A. and Ishikawa, H. Using DEA to evaluate the state of society as measured by multiple social indicators, Socio-Econ. Plan. Sci. 27(4) (1993) 257–268.
[40] Hatefi, S.M. and Torabi, S.A. A common weight MCDA–DEA approach to construct composite indicators, Ecol. Econ. 70(1) (2010) 114–120.
[41] Hatefi, S.M. and Torabi, S.A. A slack analysis framework for improv-ing composite indicators with applications to human development and sustainable energy indices, Econom. Rev. 37(3) (2018) 247–259.
[42] Hirai, T. The human development index and its evolution, In The Cre-ation of the Human Development Approach, T. Hirai, Editor. Springer International Publishing, Cham., (2017) 73–121.
[43] Holland, J. Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control and AI, The University of Michigan. Ann Arbor, MI, 1975.
[44] Jung, S., Son, J., Kim, C. and Chung, K. Efficiency Measurement Us-ing Data Envelopment Analysis (DEA) in Public Healthcare: Research Trends from 2017 to 2022. Processes, 11(3) (2023), 811.
[45] Junior, P.N.A., Mariano, E.B. and Nascimento Rebelatto, D.A. do. Us-ing data envelopment analysis to construct human development index, in Emerging Trends in the Development and Application of Composite Indicators. IGI Global, 2017, 298–323.
[46] Kelley, A.C. The Human Development Index: “Handle with Care”, Popul. Dev. Rev. 17(2) (1991) 315–324.
[47] Kovacevic, M. Review of HDI critiques and potential improvements, Hum. Dev. Res. paper, 33 (2010) 1–44.
[48] Kramer, O. Genetic algorithms, in Genetic algorithm essentials, Springer, 2017, 11–19.
[49] Krmac, E. and Mansouri Kaleibar, M. A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation, Marit. Econ. Logist. 25(4) (2023) 817–881.
[50] Kyrgiakos, L.S., Kleftodimos, G., Vlontzos, G. and Pardalos, P.M. A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability, Oper. Res. 23(7) (2023) 7.
[51] Lee, H.S., Lin, K. and Fang, H.H. A Fuzzy Multiple Objective DEA for the Human Development Index, in Knowledge-Based Intelligent Infor-mation and Engineering Systems: 10th International Conference, KES 2006, Bournemouth, UK, October 9-11, 2006. Proceedings, Part II, B. Gabrys, R.J. Howlett, and L.C. Jain, Editors., Springer Berlin Heidel-berg: Berlin, Heidelberg. 2006, 922–928.
[52] Liu, J.S., Lu, L.Y. and Lu, W.M. Research fronts in data envelopment analysis, Omega, 58 (2016) 33–45.
[53] Liu, J.S., Lu, L.Y., Lu, W.M. and Lin, B.J. A survey of DEA applica-tions, Omega, 41(5) (2013) 893–902.
[54] Liu, J.S., Lu, L.Y., Lu, W.M. and Lin, B.J. Data envelopment analysis 1978–2010: A citation-based literature survey, Omega, 41(1) (2013) 3–15.
[55] Lovell, C.K., Pastor, J.T. and Turner, J.A. Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries, Eur. J. Oper. Res. 87(3) (1995) 507–518.
[56] Lozano, S. and Gutiérrez, E. Data envelopment analysis of the human development index, Int. J. Soc. Syst. Sci. 1(2) (2008) 132–150.
[57] Lv, Y., Hu, T., Wang, G. and Wan, Z. A penalty function method based on Kuhn–Tucker condition for solving linear bilevel programming, Com-put. Appl. Math. 188(1) (2007) 808–813.
[58] Mahlberg, B. and Obersteiner, M. Remeasuring the HDI by Data En-velopement Analysis, Available at SSRN 1999372. 2001.
[59] Mahmoudi, R., Emrouznejad, A., Shetab-Boushehri, S.N. and Hejazi, S.R. The origins, development and future directions of data envelopment analysis approach in transportation systems, Socio-Econ. Plan. Sci. 69 (2020) 100672.
[60] Mariano, E.B., Ferraz, D. and Oliveira Gobbo, S.C. de. The Human De-velopment Index with Multiple Data Envelopment Analysis Approaches: A Comparative Evaluation Using Social Network Analysis, Soc. Indic. Res. (2021) 1–58.
[61] Mariano, E.B., Sobreiro, V.A. and Rebelatto, D.A.d.N. Human devel-opment and data envelopment analysis: A structured literature review, Omega, 54 (2015), 33–49.
[62] Mejía-de-Dios, J.A., Mezura-Montes, E. and Quiroz-Castellanos, M. Au-tomated parameter tuning as a bilevel optimization problem solved by a surrogate-assisted population-based approach, Appl. Intell. 2021, 1–23.
[63] Melyn, W. and Moesen, W. Towards a synthetic indicator of macroe-conomic performance: unequal weighting when limited information is available, J. Public Econ. 1991, 1–24.
[64] Paradi, J.C. and Zhu, H. A survey on bank branch efficiency and perfor-mance research with data envelopment analysis, Omega, 41(1) (2013), 61–79.
[65] Pedraja-Chaparro, F., Salinas-Jimenez, J. and Smith, P. On the role of weight restrictions in data envelopment analysis, J. Product. Anal. 8(2) (1997), 215–230.
[66] Prasetyo, A.D. and Zuhdi, U. The government expenditure efficiency towards the human development, Procedia Econ. Financ. 5 (2013), 615–622.
[67] Ramanathan, R. Evaluating the comparative performance of countries of the Middle East and North Africa: A DEA application, Socio-Econ. Plan. Sci. 40(2) (2006) 156–167.
[68] Roghanian, E., Sadjadi, S.J. and Aryanezhad, M.B. A probabilistic bi-level linear multi-objective programming problem to supply chain plan-ning, Comput. Appl. Math. 188(1) (2007) 786–800.
[69] Roll, Y., Cook, W.D. and Golany, B. Controlling factor weights in data envelopment analysis, IIE Trans. 23(1) (1991), 2–9.
70] Ruuska, S. and Miettinen, K. Constructing evolutionary algorithms for bilevel multiobjective optimization, in 2012 IEEE Congress on Evolution-ary Computation, IEEE, 2012.
[71] Schmidt, P. Frontier production functions, Econom. Rev. 4(2) (1985), 289–328.
[72] Seiford, L.M. Data envelopment analysis: The evolution of the state of the art (1978–1995), J. Product. Anal. 7 (1996), 99–137.
[73] Seiford, L.M. A bibliography for data envelopment analysis (1978–1996)., Ann. Oper. Res. 73 (1997), 393–438.
[74] Shi, C., Lu, J. and Zhang, G. An extended Kuhn–Tucker approach for linear bilevel programming, Comput. Appl. Math. 162(1) (2005), 51–63.
[75] Shi, X. and Xia, H.S. Model and interactive algorithm of bi‐level multi‐objective decision‐making with multiple interconnected decision makers, Journal of Multi‐Criteria Decision Analysis, 10(1) (2001), 27–34.
[76] Sinha, A., Malo, P. and Deb, K. A review on bilevel optimization: from classical to evolutionary approaches and applications, IEEE Trans. Evol. Comput. 22(2) (2017) 276–295.
[77] Sinha, A., Malo, P., Frantsev, A. and Deb, K. Finding optimal strate-gies in a multi-period multi-leader–follower Stackelberg game using an evolutionary algorithm, Comput. Oper. Res. 41 (2014), 374–385.
[78] Sinha, A., Malo, P., Xu, P. and Deb, K. A bilevel optimization approach to automated parameter tuning, in Proceedings of the 2014 Annual Con-ference on Genetic and Evolutionary Computation, 2014.
[79] Song, M., An, Q., Zhang, W., Wang, Z. and Wu, J. Environmental effi-ciency evaluation based on data envelopment analysis: A review, Renew. Sustain. Energy Rev. 16(7) (2012) 4465–4469.
[80] Talbi, E.G. Metaheuristics for Bi-level Optimization. Springer Berlin Heidelberg, 2013.
[81] Thanassoulis, E., De Witte, K., Johnes, J., Johnes, G., Karagiannis, G. and Portela, C.S. Applications of Data Envelopment Analysis in Edu-cation. In: Zhu, J. (eds) Data envelopment analysis: A handbook of empirical studies and applications. International Series in Operations Research & Management Science, (2016), 367–438.
[82] Thanassoulis, E., Portela, M.C. and Allen, R. Incorporating value judg-ments in DEA, Handbook on data envelopment analysis, 2004, 99–138.
[83] Thompson, R.G., Langemeier, L.N., Lee, C.T., Lee, E. and Thrall, R.M.The role of multiplier bounds in efficiency analysis with applica-tion to Kansas farming, J. Econom. 46(1-2) (1990), 93–108.
[84] Tofallis, C. Multicriteria ranking using weights which minimize the score range, In New developments in multiple objective and goal programming 2010 (pp. 133–140). Springer Berlin Heidelberg.
[85] Tofallis, C. An automatic-democratic approach to weight setting for the new human development index, J. Popul. Econ. 26(4) (2013), 1325–1345.
[86] Tone, K. A slacks-based measure of efficiency in data envelopment anal-ysis, Eur. J. Oper. Res. 130(3) (2001), 498–509.
[87] UNDP, Human Development Report (1990), New York: United Nations Development Programme, Oxford University Press, 1990.
[88] UNDP, Human Development Report 2010: 20th Anniversary Edition, Palgrave Macmillan, 2010.
[89] Van Puyenbroeck, T. and Rogge, N. Comparing regional human devel-opment using global frontier difference indices, Socio-Econ. Plan. Sci. 70 (2020) 100663.
[90] Vicente, L., Savard, G. and Júdice, J. Descent approaches for quadratic bilevel programming, J. Optim. Theory Appl. 81(2) (1994), 379–399.
[91] Wong, Y.H. and Beasley, J. Restricting weight flexibility in data envel-opment analysis, J. Oper. Res. Soc. 1990, 829–835.
[92] Yan, J., Li, L., Zhao, F., Zhang, F. and Zhao, Q. A multi-level optimiza-tion approach for energy-efficient flexible flow shop scheduling, J. Clean. Prod. 137 (2016), 1543–1552.
[93] Zhou, P., Ang, B.W. and Poh, K.L. A mathematical programming ap-proach to constructing composite indicators, Ecol. Econ. 62(2) (2007), 291–297.
[94] Zhou, P., Ang, B.W. and Poh, K.L. A survey of data envelopment anal-ysis in energy and environmental studies, Eur. J. Oper. Res. 189(1) (2008), 1–18.
[95] Zhou, P., Ang, B.W. and Zhou, D.Q. Weighting and Aggregation in Com-posite Indicator Construction: a Multiplicative Optimization Approach, Soc. Indic. Res. 96(1) (2010), 169–181.
[96] Zhou, H., Yang, Y., Chen, Y. and Zhu, J. Data envelopment analysis application in sustainability: The origins, development and future direc-tions, Eur. J. Oper. Res. 264(1) (2018) 1–16.
[97] Zimmermann, S., Hakimifard, G., Zamora, M., Poranne, R. and Coros, S. A multi-level optimization framework for simultaneous grasping and motion planning, IEEE Robot. Autom. Lett. 5(2) (2020) 2966–2972.