An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights

As the biggest rigid constraint for high-quality economic and social development, how to improve the carrying capacity of water resources, realize the stable and coordinated development of water resources-ecological environment-economic and social integrated system, and provide water resources guara...

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Main Authors: Fei Li, Guang Zhang, Shaohua Hu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2022/3329628
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author Fei Li
Guang Zhang
Shaohua Hu
author_facet Fei Li
Guang Zhang
Shaohua Hu
author_sort Fei Li
collection DOAJ
description As the biggest rigid constraint for high-quality economic and social development, how to improve the carrying capacity of water resources, realize the stable and coordinated development of water resources-ecological environment-economic and social integrated system, and provide water resources guarantee for regional transformation and upgrading development is a major issue in the current social development. This paper firstly selects the minimum loss of water resources allocation as the objective function for mathematical modelling, chooses the particle swarm algorithm as the objective algorithm, and proposes a particle swarm algorithm based on the standard particle swarm algorithm with improved adaptive decreasing inertia weights. It is a time-varying process for the inertia weights and acceleration factors of the standard particle swarm algorithm so that they change nonlinearly with the continuous advancement of the iterative optimization seeking process, thus improving the convergence accuracy and speed of the algorithm and reducing the risk of falling into local optimum solutions at a later stage. Finally, based on the actual installation of the current water distribution reactive power compensation device, the shunt distributor set is selected as the reactive power compensation device, sensitivity analysis is applied to the load nodes for sensitivity calculation, and the nodes requiring compensation are connected to the shunt distributor set for flexible and optimal configuration. The stronger local search capability of the inertia weight adaptive decreasing algorithm is utilized in the generation process of new particles to perform a local search operation for particles, which avoids premature convergence and improves the search performance of the algorithm. To realize the rational allocation of water resources, a multiobjective receiving area water resources optimization allocation model with maximum water supply benefit, minimum regional water shortage, and minimum pollutant emission is established.
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institution Kabale University
issn 2042-3195
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publishDate 2022-01-01
publisher Wiley
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series Journal of Advanced Transportation
spelling doaj-art-bd1655096d7d4bf0a8f21aba7a4c98732025-02-03T06:05:48ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/3329628An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia WeightsFei Li0Guang Zhang1Shaohua Hu2School of Safety Science and Emergency ManagementSchool of Safety Science and Emergency ManagementSchool of Safety Science and Emergency ManagementAs the biggest rigid constraint for high-quality economic and social development, how to improve the carrying capacity of water resources, realize the stable and coordinated development of water resources-ecological environment-economic and social integrated system, and provide water resources guarantee for regional transformation and upgrading development is a major issue in the current social development. This paper firstly selects the minimum loss of water resources allocation as the objective function for mathematical modelling, chooses the particle swarm algorithm as the objective algorithm, and proposes a particle swarm algorithm based on the standard particle swarm algorithm with improved adaptive decreasing inertia weights. It is a time-varying process for the inertia weights and acceleration factors of the standard particle swarm algorithm so that they change nonlinearly with the continuous advancement of the iterative optimization seeking process, thus improving the convergence accuracy and speed of the algorithm and reducing the risk of falling into local optimum solutions at a later stage. Finally, based on the actual installation of the current water distribution reactive power compensation device, the shunt distributor set is selected as the reactive power compensation device, sensitivity analysis is applied to the load nodes for sensitivity calculation, and the nodes requiring compensation are connected to the shunt distributor set for flexible and optimal configuration. The stronger local search capability of the inertia weight adaptive decreasing algorithm is utilized in the generation process of new particles to perform a local search operation for particles, which avoids premature convergence and improves the search performance of the algorithm. To realize the rational allocation of water resources, a multiobjective receiving area water resources optimization allocation model with maximum water supply benefit, minimum regional water shortage, and minimum pollutant emission is established.http://dx.doi.org/10.1155/2022/3329628
spellingShingle Fei Li
Guang Zhang
Shaohua Hu
An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
Journal of Advanced Transportation
title An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
title_full An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
title_fullStr An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
title_full_unstemmed An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
title_short An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
title_sort algorithm for optimal allocation of water resources in receiving areas based on adaptive decreasing inertia weights
url http://dx.doi.org/10.1155/2022/3329628
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