IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v28y2020i1d10.1007_s10100-018-0566-3.html
   My bibliography  Save this article

A novel mixed Spider’s web initial solution and data envelopment analysis for solving multi-objective optimization problems

Author

Listed:
  • Kourosh Ranjbar

    (Payame Noor University)

  • Hamid Khaloozadeh

    (K.N. Toosi University of Technology)

  • Aghileh Heydari

    (Payame Noor University)

Abstract

When it comes to solving engineering design problems, the existing techniques require a significant amount of time. In the following case the objective function value has been obtained using optimization methods which has been the subject of many research efforts, recently accepted methods possess advantages however the biggest challenge is the number of objective functions and constraints required. In this paper, we proposed a novel combined approach involving the method of Data Envelopment Analysis and the Spider’s web initial solution. It turns out that the selected method requires no additional algorithm and can be used to solve most multi-objective problems, in contrast to previous methods in which the number of objective functions increase due to a rising level of complexity in such algorithms thereby leading to a reduction in effectiveness. Furthermore the proposed method is capable of yielding a more efficient result in non-convex problems as well as typical convex problems.

Suggested Citation

  • Kourosh Ranjbar & Hamid Khaloozadeh & Aghileh Heydari, 2020. "A novel mixed Spider’s web initial solution and data envelopment analysis for solving multi-objective optimization problems," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 193-208, March.
    • Handle: RePEc:spr:cejnor:v:28:y:2020:i:1:d:10.1007_s10100-018-0566-3
    DOI: 10.1007/s10100-018-0566-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10100-018-0566-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10100-018-0566-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Fuh-Hwa Franklin & Huang, Chueng-Chiu & Yen, Yu-Lee, 2000. "Using DEA to obtain efficient solutions for multi-objective 0-1 linear programs," European Journal of Operational Research, Elsevier, vol. 126(1), pages 51-68, October.
    2. Henry Tulkens, 2006. "On FDH Efficiency Analysis: Some Methodological Issues and Applications to Retail Banking, Courts and Urban Transit," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 311-342, Springer.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Yougbare, Jacob W. & Teghem, Jacques, 2007. "Relationships between Pareto optimality in multi-objective 0-1 linear programming and DEA efficiency," European Journal of Operational Research, Elsevier, vol. 183(2), pages 608-617, December.
    5. Yun, Y. B. & Nakayama, H. & Tanino, T. & Arakawa, M., 2001. "Generation of efficient frontiers in multi-objective optimization problems by generalized data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 129(3), pages 586-595, March.
    6. Yeboon Yun & Hirotaka Nakayama, 2013. "Utilizing expected improvement and generalized data envelopment analysis in multi-objective genetic algorithms," Journal of Global Optimization, Springer, vol. 57(2), pages 367-384, October.
    7. Lin, Rung-Chuan & Sir, Mustafa Y. & Pasupathy, Kalyan S., 2013. "Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services," Omega, Elsevier, vol. 41(5), pages 881-892.
    8. Yun, Y. B. & Nakayama, H. & Arakawa, M., 2004. "Multiple criteria decision making with generalized DEA and an aspiration level method," European Journal of Operational Research, Elsevier, vol. 158(3), pages 697-706, November.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yeboon Yun & Hirotaka Nakayama & Min Yoon, 2016. "Generation of Pareto optimal solutions using generalized DEA and PSO," Journal of Global Optimization, Springer, vol. 64(1), pages 49-61, January.
    2. Ravelojaona, Paola, 2019. "On constant elasticity of substitution – Constant elasticity of transformation Directional Distance Functions," European Journal of Operational Research, Elsevier, vol. 272(2), pages 780-791.
    3. Harald Dyckhoff & Katrin Allen, 1999. "Theoretische Begründung einer Effizienzanalyse mittels Data Envelopment Analysis (DEA)," Schmalenbach Journal of Business Research, Springer, vol. 51(5), pages 411-436, May.
    4. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    5. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    6. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    7. Kuosmanen, Timo & Post, Thierry, 2001. "Measuring economic efficiency with incomplete price information: With an application to European commercial banks," European Journal of Operational Research, Elsevier, vol. 134(1), pages 43-58, October.
    8. Krüger, Jens J., 2018. "Direct targeting of efficient DMUs for benchmarking," International Journal of Production Economics, Elsevier, vol. 199(C), pages 1-6.
    9. Giokas, Dimitris I., 2008. "Assessing the efficiency in operations of a large Greek bank branch network adopting different economic behaviors," Economic Modelling, Elsevier, vol. 25(3), pages 559-574, May.
    10. Lin, Rung-Chuan & Sir, Mustafa Y. & Pasupathy, Kalyan S., 2013. "Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services," Omega, Elsevier, vol. 41(5), pages 881-892.
    11. De Luca Cardillo, Dorotea & Fortuna, Tiziana, 2000. "A DEA model for the efficiency evaluation of nondominated paths on a road network," European Journal of Operational Research, Elsevier, vol. 121(3), pages 549-558, March.
    12. Peter Bogetoft & Dexiang Wang, 2005. "Estimating the Potential Gains from Mergers," Journal of Productivity Analysis, Springer, vol. 23(2), pages 145-171, May.
    13. Yun, Y. B. & Nakayama, H. & Tanino, T., 2004. "A generalized model for data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 157(1), pages 87-105, August.
    14. Peter Bogetoft & Joseph M. Tama & Jørgen Tind, 2000. "Convex Input and Output Projections of Nonconvex Production Possibility Sets," Management Science, INFORMS, vol. 46(6), pages 858-869, June.
    15. Aude Hubrecht-Deville, 2007. "Branch banking networks assessment using DEA:A benchmarking analysis," Working Papers CREGO 1071103, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    16. Talluri, Srinivas & Narasimhan, Ram, 2004. "A methodology for strategic sourcing," European Journal of Operational Research, Elsevier, vol. 154(1), pages 236-250, April.
    17. Yang, Chyan & Liu, Hsian-Ming, 2012. "Managerial efficiency in Taiwan bank branches: A network DEA," Economic Modelling, Elsevier, vol. 29(2), pages 450-461.
    18. Miranda, Rafael de Carvalho & Montevechi, José Arnaldo Barra & da Silva, Aneirson Francisco & Marins, Fernando Augusto Silva, 2017. "Increasing the efficiency in integer simulation optimization: Reducing the search space through data envelopment analysis and orthogonal arrays," European Journal of Operational Research, Elsevier, vol. 262(2), pages 673-681.
    19. Keshvari, Abolfazl & Kuosmanen, Timo, 2013. "Stochastic non-convex envelopment of data: Applying isotonic regression to frontier estimation," European Journal of Operational Research, Elsevier, vol. 231(2), pages 481-491.
    20. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:cejnor:v:28:y:2020:i:1:d:10.1007_s10100-018-0566-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.