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A linear bi-level multi-objective program for optimal allocation of water resources

Author

Listed:
  • Ijaz Ahmad
  • Fan Zhang
  • Junguo Liu
  • Muhammad Naveed Anjum
  • Muhammad Zaman
  • Muhammad Tayyab
  • Muhammad Waseem
  • Hafiz Umar Farid

Abstract

This paper presents a simple bi-level multi-objective linear program (BLMOLP) with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader) in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers) in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON) technique which creates a compromise between upper and lower level decision makers (DMs), and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Suggested Citation

  • Ijaz Ahmad & Fan Zhang & Junguo Liu & Muhammad Naveed Anjum & Muhammad Zaman & Muhammad Tayyab & Muhammad Waseem & Hafiz Umar Farid, 2018. "A linear bi-level multi-objective program for optimal allocation of water resources," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-25, February.
    • Handle: RePEc:plo:pone00:0192294
    DOI: 10.1371/journal.pone.0192294
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    1. Ali Zarei & Sayed-Farhad Mousavi & Madjid Eshaghi Gordji & Hojat Karami, 2019. "Optimal Reservoir Operation Using Bat and Particle Swarm Algorithm and Game Theory Based on Optimal Water Allocation among Consumers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3071-3093, July.

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