A multiobjective fuzzy linear programming model for sustainable integrated operation of a multireservoir system

Arunkumar, R.; Jothiprakash, V.

doi:10.1111/lre.12136

Cited by 10 publications

(4 citation statements)

References 30 publications

(30 reference statements)

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“…Fuzzy logic was identified as an appropriate tool to address the uncertainty due to imprecision in defining the goals of the stakeholders [29]. In this context, fuzzy water allocation models to address the uncertainty due to imprecision in defining the goals of the reservoir users has been widely used all over the world [46] and in India [47][48][49]. A typical fuzzy optimization model for reservoir operation works on specifying the goals of the users as fuzzy membership functions and the mathematical formulation of a typical reservoir operation as a water quantity control model, following Rehana and Mujumdar [4], which can be expressed as follows:…”

Section: Reservoir Operation and Associated Uncertaintiesmentioning

confidence: 99%

“…In this context, fuzzy rule-based reservoir operation models have gained interest to address the uncertainty due to impression in specifying the goals of various reservoir users [50]. Many researchers adopted fuzzy optimization models for optimum water quantity allocations in reservoir operation [45,48,49,51]. A fuzzy rule-based model was developed by Panigrahi and Mujumdar [45] for Malaprabha irrigation reservoir in Karnataka, a single purpose reservoir, where the fuzzy membership functions have been constructed for inflow, storage, demand and release.…”

Section: Reservoir Operation and Associated Uncertaintiesmentioning

confidence: 99%

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Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

Rehana

Rajulapati

Ghosh

et al. 2020

Water

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Regional water resource modelling is important for evaluating system performance by analyzing the reliability, resilience and vulnerability criteria of the system. In water resource systems modelling, several uncertainties abound, including data inadequacy and errors, modeling inaccuracy, lack of knowledge, imprecision, inexactness, randomness of natural phenomena, and operational variability, in addition to challenges such as growing population, increasing water demands, diminishing water sources and climate change. Recent advances in modelling techniques along with high computational capabilities have facilitated rapid progress in this area. In India, several studies have been carried out to understand and quantify uncertainties in various basins, enumerate large temporal and regional mismatches between water availability and demands, and project likely changes due to warming. A comprehensive review of uncertainties in water resource modelling from an Indian perspective is yet to be done. In this work, we aim to appraise the quantification of uncertainties in systems modelling in India and discuss various water resource management and operation models. Basic formulation of models for probabilistic, fuzzy and grey/inexact simulation, optimization, and multi-objective analyses to water resource design, planning and operations are presented. We further discuss challenges in modelling uncertainties, missing links in integrated systems approach, along with directions for future.

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Section: Reservoir Operation and Associated Uncertaintiesmentioning

confidence: 99%

Section: Reservoir Operation and Associated Uncertaintiesmentioning

confidence: 99%

Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

Rehana

Rajulapati

Ghosh

et al. 2020

Water

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“…The obtained results revealed that the average operator gives maximum irrigation intensity as compared to the max-min and TPMOFLP models. Arunkumar and Jothiprakash (2016) applied Multiobjective fuzzy linear programming approach with the objectives of minimization of Net benefits and crop production. This methodology is validated to the case study of Kukadi Irrigation project (KIP) in Maharashtra, India.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Intuitionistic Fuzzy Optimization Approach in Optimal Irrigation Planning and Operation of Reservoir

Pawar

Patel

Mirajkar

2023

Water Resour Manage

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The present study includes the formulation of a Multiobjective Intuitionistic Fuzzy Linear Programming model for optimal scheduling of crops in the command area of the Ukai-Kakrapar Irrigation project, Gujarat, India. The crisp linear programming approach has been used to obtain the optimal solutions of four conflicting objectives, viz., maximization of net irrigation benefits, employment generation, minimization of cost of cultivation, and maximization of revenue generation from industrial and municipal supplies. The crisp solutions were, in turn, used to develop Intuitionistic Fuzzy Optimization Multiobjective fuzzy linear programming (IFO MOFLP), IFO MOFLP with hesitation index, and two-phase IFO MOFLP (TPIFO MOFLP) models. The performance of IFO MOFLP, IFO MOFLP with hesitation index, and TPIFO MOFLP models are compared in terms of the degree of acceptance, degree of rejection, and hesitation index for inflows at 75% probability of exceedance. The results obtained from IFO MOFLP, IFO MOFLP with hesitation index, and TPIFO MOFLP are also compared with the Compromised MOFLP (Average Operator Case-I) solutions given by Mirajkar and Patel (2016) for the same command area. The irrigation intensity for the entire command area from the proposed TPIFO MOFLP model (112.19%) is considerably higher than those obtained from the Average Operator Case-I (104.60%) model proposed by Mirajkar and Patel (2016). The net irrigation benefits, employment generation, cost of cultivation, and revenue generation from municipal and industrial supplies, resulting from the proposed TPIFO MOFLP model are Rs 10,836.19 million, 34,980.4 thousand workdays, Rs 5,672.23 million, and Rs 2,314.03 million, respectively along with the degree of acceptance, α=0.68, degree of rejection, β =0.19 and degree of hesitation, π =0.13. The corresponding values reported from the Compromised MOFLP model (Average Operator Case-I) (Mirajkar and Patel,2016) were Rs 11,058.27 million, 33,414.62 thousand workdays, Rs 5,622.20 million, and Rs 2,686.25 million, respectively. The releases from the reservoir corresponding to the proposed TPIFO MOFLP model are comparatively lesser than the Compromised MOFLP (Average Operator Case-I) model,indicating the optimal allocation of available water in the command area. Apart from giving better values of selected objective functions, the proposed model also gives additional uncertainty measures like degree of acceptance, degree of rejection, and degree of hesitation which would help the planner to make better decisions for a real-world problem.

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“…The model consists of a crop water allocation model and an operating policy model developed with deterministic dynamic programming. Arunkumaret al [16] also developed a DP model to solve the problem of water delivery from two reservoirs to an irrigation district at once. Predicted information is updated in the model, including evapotranspiration from crops, evaporation from reservoirs, and inflows.…”

Section: Introductionmentioning

confidence: 99%

Optimal reservoir operation policy determination for uncertainty conditions

Choudhari¹,

Kumbhalkar²,

Bhise³

et al. 2022

3C Empresa

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In recent years, optimising reservoir operations has emerged as a hot topic in the field of water resources management. Heuristic approaches to reservoir operation that incorporate rule curves and, to some extent, operator discretion have been the norm in the past. With so many stakeholders involved in water management, it can be difficult to strike a happy medium between everyone's needs and wants. The dissertation proposes a method for transforming traditional reservoir operation into optimal strategies, allowing users to take advantage of the rapid development of computational techniques. This research creates and applies a Multi Objective Fuzzy Linear Programming (MOFLP) model to the monthly operating policies of the stage-I Jayakwadi reservoir located on the Godavari, the largest river in the Indian state of Maharashtra. In order to formulate the problem, we use two objective functions—maximizing irrigation releases and maximising power production releases. The constraints of the study are considered, including turbine release, irrigation demand, reservoir storage capacity, and continuity of reservoir storage. Utilizing linear membership functions, the objective functions are fuzzily defined. All other model parameters except for the goals are assumed to be hard and fast rules. Maximum Happiness Operating Policy (MOFLP) was used to determine the best course of action.

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A multiobjective fuzzy linear programming model for sustainable integrated operation of a multireservoir system

Cited by 10 publications

References 30 publications

Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

Multiobjective Intuitionistic Fuzzy Optimization Approach in Optimal Irrigation Planning and Operation of Reservoir

Optimal reservoir operation policy determination for uncertainty conditions

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