Economic benefit evaluation of water resources allocation in transboundary basins based on particle swarm optimization algorithm and cooperative game model—A case study of Lancang-Mekong River Basin

Bi, Fei; Zhou, Hongbo; Zhu, Min; Wang, Weiwei

doi:10.1371/journal.pone.0265350

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…The PSO algorithm is simple in structure and fast in convergence, which is suitable for scheduling; however, the PSO is prone to the local optimum, with fast convergence necessitating that the global search be performed first. When an optimal solution is determined within a specific range, the local search ability is used to search for the optimal solution position [ 21 ]. Given the PSO’s unassuming and easy implementation characteristics, it is used to solve the problem of resource optimisation in IoT.…”

Section: Related Work and Motivationmentioning

confidence: 99%

Effects of Particle Swarm Optimisation on a Hybrid Load Balancing Approach for Resource Optimisation in Internet of Things

Datiri

2023

Sensors

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The internet of things, a collection of diversified distributed nodes, implies a varying choice of activities ranging from sleep monitoring and tracking of activities, to more complex activities such as data analytics and management. With an increase in scale comes even greater complexities, leading to significant challenges such as excess energy dissipation, which can lead to a decrease in IoT devices’ lifespan. Internet of things’ (IoT) multiple variable activities and ample data management greatly influence devices’ lifespan, making resource optimisation a necessity. Existing methods with respect to aspects of resource management and optimisation are limited in their concern of devices energy dissipation. This paper therefore proposes a decentralised approach, which contains an amalgamation of efficient clustering techniques, edge computing paradigms, and a hybrid algorithm, targeted at curbing resource optimisation problems and life span issues associated with IoT devices. The decentralised topology aimed at the resource optimisation of IoT places equal importance on resource allocation and resource scheduling, as opposed to existing methods, by incorporating aspects of the static (round robin), dynamic (resource-based), and clustering (particle swarm optimisation) algorithms, to provide a solid foundation for an optimised and secure IoT. The simulation constructs five test-case scenarios and uses performance indicators to evaluate the effects the proposed model has on resource optimisation in IoT. The simulation results indicate the superiority of the PSOR2B to the ant colony, the current centralised optimisation approach, LEACH, and C-LBCA.

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Section: Related Work and Motivationmentioning

confidence: 99%

Effects of Particle Swarm Optimisation on a Hybrid Load Balancing Approach for Resource Optimisation in Internet of Things

Datiri

2023

Sensors

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“…The basic water demand and basic electricity demand [6] are taken as a second basic constraints of water resources scheduling [7] in the two lakes. The water supply constraint is as follows:…”

Section: Constraint Conditionsmentioning

confidence: 99%

Sensitivity analysis of underwater control system based on IA-PSO

2023

Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023)

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In the southwestern United States, Lakes Powell and Lake Mead are taking the responsibility of supplying water and generating electricity to the surrounding five states of Arizona (AZ), California (CA), Wyoming (WY), New Mexico (NM), and Colorado (CO). Accordingly, we have established three models, and have established them and conducted sensitivity analysis combined with changes of various conditions in reality. In combination with multiple water supply needs, Model 1 optimizes the economic benefits from water and power supply of the five states as objective functions. In setting the constraints, the model takes into account such factors as water balance, minimum demand for water and power supplies, lake level requirements, and issues of sovereignty in downstream Mexico. Considering the influence of seasons on various factors, the decision variables are the water supply flow and power supply flow of each state on a quarterly basis. When solving the model, IA-PSO is used for optimization, reducing the possibility of local optimal solution.The optimization result is the optimal distribution of the power and water supply flows provided by the two lakes to the states over the four quarters of a year. In the case of CO,when the supply exceeds the demand, the time to provide the optimized water supply flow to meet its one-quarter water consumption demand is calculated to be 57.5 days; while when the supply fails to meet the demand, the additional water supplement required is 0.8×109m3.

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“…The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/land12091698/s1, Supplementary File S1: GEP accounting system; Supplementary File S2: Model parameter and input. References [43][44][45] are cited in the supplementary materials.…”

Section: Supplementary Materialsmentioning

confidence: 99%

System Dynamics-Based Game Theoretical Analysis for Watershed Eco-Compensation Design: A Case Study in Tuojiang River, Sichuan Province, China

Min,

Yu,

Zhao

et al. 2023

Land

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Eco-compensation is an important policy tool to trade off economic development and environmental protection in a watershed. This study introduced the gross ecosystem product (GEP) accounting system to identify the eco-compensation provider (ECP) and eco-compensation receiver (ECR) of a river basin. Then, a cooperative game model and a non-cooperative game model between the ECP and the ECR were established, in which system dynamics was incorporated into the game theoretical analysis to aid selection of the optimal compensation scheme. The study further demonstrated the model applications by taking the Tuojiang River Basin as a case. The results showed that the accounted GEP increased from CNY 32.2 billion in 2018 to CNY 35.5 billion in 2020, with a growth rate of 10.2%. Deyang City, as an ECP, had a cumulative difference of CNY 11.759 billion between its accounted GEP and actual GEP output over the three years. Neijiang City, Zigong City, and Luzhou City were taken as the ECR, receiving the GEP revenues as CNY 11.289 billion, 7.661 billion, and 1.497 billion, respectively. Chengdu City changed from the ECP to the ECR and ultimately to the ECP. However, Ziyang City and Meishan City changed from the ECP to the ECR. The eco-compensations increased to varying degrees during 2018–2020 in both game scenarios, with ECP payments and ECR revenues increasing by 16.5% and 4.6% in the non-cooperative game and by 5.0% and 50.8% in the cooperative game. Particularly, the eco-compensation obtained by the cooperative game had better environmental and economic performance, as there was a total of CNY 7.049 billion being saved. However, there was no savings of compensation by the non-cooperative game. It is expected that the results may provide insight into the design of the eco-compensation standard for a river basin.

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Economic benefit evaluation of water resources allocation in transboundary basins based on particle swarm optimization algorithm and cooperative game model—A case study of Lancang-Mekong River Basin

Cited by 5 publications

References 30 publications

Effects of Particle Swarm Optimisation on a Hybrid Load Balancing Approach for Resource Optimisation in Internet of Things

Effects of Particle Swarm Optimisation on a Hybrid Load Balancing Approach for Resource Optimisation in Internet of Things

Sensitivity analysis of underwater control system based on IA-PSO

System Dynamics-Based Game Theoretical Analysis for Watershed Eco-Compensation Design: A Case Study in Tuojiang River, Sichuan Province, China

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