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Conic scalarization approach to solve multi-choice multi-objective transportation problem with interval goal

Author

Listed:
  • Sankar Kumar Roy

    (Vidyasagar University)

  • Gurupada Maity

    (Vidyasagar University)

  • Gerhard Wilhelm Weber

    (Middle East Technical University)

  • Sirma Zeynep Alparslan Gök

    (Suleyman Demirel University)

Abstract

This paper explores the study of multi-choice multi-objective transportation problem (MCMTP) under the light of conic scalarizing function. MCMTP is a multi-objective transportation problem (MOTP) where the parameters such as cost, demand and supply are treated as multi-choice parameters. A general transformation procedure using binary variables is illustrated to reduce MCMTP into MOTP. Most of the MOTPs are solved by goal programming (GP) approach, but the solution of MOTP may not be satisfied all times by the decision maker when the objective functions of the proposed problem contains interval-valued aspiration levels. To overcome this difficulty, here we propose the approaches of revised multi-choice goal programming (RMCGP) and conic scalarizing function into the MOTP, and then we compare among the solutions. Two numerical examples are presented to show the feasibility and usefulness of our paper. The paper ends with a conclusion and an outlook on future studies.

Suggested Citation

  • Sankar Kumar Roy & Gurupada Maity & Gerhard Wilhelm Weber & Sirma Zeynep Alparslan Gök, 2017. "Conic scalarization approach to solve multi-choice multi-objective transportation problem with interval goal," Annals of Operations Research, Springer, vol. 253(1), pages 599-620, June.
    • Handle: RePEc:spr:annopr:v:253:y:2017:i:1:d:10.1007_s10479-016-2283-4
    DOI: 10.1007/s10479-016-2283-4
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    Cited by:

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    7. P. Kumar & A. K. Bhurjee, 2022. "Multi-objective enhanced interval optimization problem," Annals of Operations Research, Springer, vol. 311(2), pages 1035-1050, April.
    8. Zheng, Xiao-Xue & Chang, Ching-Ter, 2021. "Topology design of remote patient monitoring system concerning qualitative and quantitative issues," Omega, Elsevier, vol. 98(C).
    9. Firoz Ahmad & Ahmad Yusuf Adhami, 2019. "Total cost measures with probabilistic cost function under varying supply and demand in transportation problem," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 583-602, June.
    10. Gurupada Maity & Sankar Kumar Roy & Jose Luis Verdegay, 2019. "Time Variant Multi-Objective Interval-Valued Transportation Problem in Sustainable Development," Sustainability, MDPI, vol. 11(21), pages 1-15, November.
    11. Soheyl Khalilpourazari & Shima Soltanzadeh & Gerhard-Wilhelm Weber & Sankar Kumar Roy, 2020. "Designing an efficient blood supply chain network in crisis: neural learning, optimization and case study," Annals of Operations Research, Springer, vol. 289(1), pages 123-152, June.
    12. Sonia Singh & Shalabh Singh, 2018. "Bi-criteria transportation problem with multiple parameters," Annals of Operations Research, Springer, vol. 269(1), pages 667-692, October.

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