Prospect Theory in Particle Swarm Optimization for Constraints Nonlinear Optimization Problems

Abdulkareem, Ahmed Ibraheem; Dhahad, Hayder A.; Yousif, Noor Q.

doi:10.1109/scee.2018.8684144

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2022

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“…The challenge of CHs-selection is an NP-hard optimization problem and traditional optimization approaches are inefficient as the network grows in size [8]. PSO is among the effective nature-inspired algorithms to select optimum solutions due to its ease of use for NP-hard issues [9], capacity to escape the local optimum, outstanding solution quality, and quick convergence [10].…”

Section: Introductionmentioning

confidence: 99%

Increase the WSN-Lifespan Used in Monitoring Forest Fires by PSO

Al-Hilfi¹,

Al-Nayar²

2022

MMEP

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The Wireless Sensor Networks (WSNs) have become the most cost-effective monitoring solution due to their low cost, despite their major drawback of limited power due to dependence on batteries. Clustering is one of the successful solutions for extending the life of the WSN. Where optimal CH selection results in an increase in the lifetime of WSN. The paper discusses a strategy for field deployment of nodes in the form of clusters and a method for Cluster Head (CH) selection using Particle Swarm Optimization (PSO). The method employs a fitness function to select the optimum CHs for cluster nodes. This paper simulates a case study for the early detection of forest fires and demonstrates how to extend the lifetime of a WSN by utilizing the proposed PSO algorithm.

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Section: Introductionmentioning

confidence: 99%