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Total cost measures with probabilistic cost function under varying supply and demand in transportation problem

Author

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  • Firoz Ahmad

    (Aligarh Muslim University)

  • Ahmad Yusuf Adhami

    (Aligarh Muslim University)

Abstract

In the present competitive world, it is often said that “Time is Money” in almost every aspect of life. Time is a factor which affects the various real-life problems directly or indirectly. So, in order to incorporate the “time” as a factor in transportation problems (TPs), we have considered the probabilistic cost/profit function termed as “survival cost/profit” which is again a time-dependent function. In this study, we have assumed that the supply and demand quantities are varying between some specified intervals. Due to the variation in the supply and demand quantities, the value of the objective function is also obtained between interval which is bounded by lower and upper values. Based on the above-stated assumptions, we have developed a couple of mathematical optimization models for the TPs. The solution procedure has also been discussed to solve the proposed mathematical models. At last, a numerical illustration has been presented to show the validity of the model and solution procedure which is helpful in the decision-making process.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:opsear:v:56:y:2019:i:2:d:10.1007_s12597-019-00364-5
    DOI: 10.1007/s12597-019-00364-5
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    References listed on IDEAS

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    1. Animesh Biswas & Nilkanta Modak, 2017. "On Solving Multiobjective Transportation Problems with Fuzzy Random Supply and Demand Using Fuzzy Goal Programming," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 8(3), pages 54-81, July.
    2. 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.
    3. Liu, Shiang-Tai, 2003. "The total cost bounds of the transportation problem with varying demand and supply," Omega, Elsevier, vol. 31(4), pages 247-251, August.
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    Cited by:

    1. Shafiq Ahmad & Firoz Ahmad & Intekhab Alam & Abdelaty Edrees Sayed & Mali Abdollahian, 2022. "Modeling and Optimizing the System Reliability Using Bounded Geometric Programming Approach," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
    2. Prachi Agrawal & Talari Ganesh, 2020. "Fuzzy fractional stochastic transportation problem involving exponential distribution," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1093-1114, December.
    3. Firoz Ahmad, 2022. "Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management," Annals of Operations Research, Springer, vol. 311(2), pages 551-585, April.
    4. Md. Ashraful Babu & M. A. Hoque & Md. Sharif Uddin, 2020. "A heuristic for obtaining better initial feasible solution to the transportation problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 221-245, March.
    5. Ahmad, Firoz & Alnowibet, Khalid A. & Alrasheedi, Adel F. & Adhami, Ahmad Yusuf, 2022. "A multi-objective model for optimizing the socio-economic performance of a pharmaceutical supply chain," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).

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