A multi-objective bi-level stochastic programming for water sustainable supply and allocation problem

Document Type : Research Paper


Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran


In recent years, the existence of some challenges in the water industry has led organizations to design and implement various solutions. This paper seeks to propose a methodology to address some of the most important challenges such as water sustainable supply and allocation (WSSA) problem, type of decision-making approach, coordination, sustainability, and uncertainty. The proposed methodology focuses on solving the WSSA problem, by considering these challenges in the problem. Concerning the conflict between sectors benefits of water resources and consumption and the need for coordinating between them, in this paper the type of decision-making approach is based on coordination and because of the existence of conflicting goals in important areas of water management decision making, a multi-objective bi-level programming model is presented. At the model leader level, the water supply management problem and the follower level, the water allocation management problem with multiple objectives is formulated, so that some of the parameters are assumed to be random and normally distributed. Also, a hybrid model based on chance-constrained programming (CCP) and nadir compromise programming (NCP) models as a deterministic transformation to bi-level stochastic programming model is proposed and a bi-level genetic algorithm is used to solve it. The proposed model is illustrated to solve a real problem in water resources and consumption management of Tehran city and based on several scenarios, the results are analyzed. The results show that the proposed methodology presents a suitable solution for addressing the mentioned challenges in the decision-making and planning process in the water management.


Main Subjects

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  • Receive Date: 27 April 2021
  • Revise Date: 23 February 2022
  • Accept Date: 24 February 2022
  • First Publish Date: 24 February 2022