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

Ijaz Ahmad1,2, Fan Zhang2,3,4, Junguo Liu5

  • 1Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore, Pakistan.

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|February 15, 2018
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Summary
This summary is machine-generated.

This study introduces a bi-level multi-objective linear program (BLMOLP) for optimal water resource allocation. The simultaneous compromise constraint (SICCON) technique effectively balances competing water user demands, maximizing societal benefits.

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Area of Science:

  • Water Resource Management
  • Operations Research
  • Environmental Engineering

Background:

  • Optimal allocation of limited water resources is critical for societal benefit.
  • Hierarchical decision-making structures exist between water managers and user sectors.
  • Multi-objective optimization is essential for balancing competing demands.

Purpose of the Study:

  • To develop and apply a bi-level multi-objective linear program (BLMOLP) for optimal water resource allocation.
  • To introduce the simultaneous compromise constraint (SICCON) technique for solving BLMOLP.
  • To evaluate the model's applicability in the Swat River basin, Pakistan.

Main Methods:

  • Formulation of a bi-level multi-objective linear program (BLMOLP).
  • Application of the simultaneous compromise constraint (SICCON) technique to transform the problem.
  • Case study application in the Swat River basin, Pakistan, with scenario development.

Main Results:

  • The SICCON technique provides a simple, applicable, and feasible method for solving BLMOLP.
  • The developed model effectively allocates water resources among competing sectors.
  • The optimization model demonstrates practicality and efficiency under various conditions and priorities.

Conclusions:

  • The BLMOLP model with SICCON is a viable approach for complex water resource allocation problems.
  • The model successfully balances the objectives of reservoir managers and water use sectors.
  • The approach is efficient and practical for real-world water management scenarios.