Related Experiment Video
Updated: Oct 12, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Game theory and evolutionary optimization approaches applied to resource allocation problems in computing
Shahab Shamshirband1, Javad Hassannataj Joloudari2,3, Sahar Khanjani Shirkharkolaie3
1Future Technology Research Center, College of Future, National Yunlin University of Science and Technology 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan.
Abstract:
Today's intelligent computing environments, including the Internet of Things (IoT), Cloud Computing (CC), Fog Computing (FC), and Edge Computing (EC), allow many organizations worldwide to optimize their resource allocation regarding the quality of service and energy consumption. Due to the acute conditions of utilizing resources by users and the real-time nature of the data, a comprehensive and integrated computing environment has not yet provided a robust and reliable capability for proper resource allocation. Although traditional resource allocation approaches in a low-capacity hardware resource system are efficient for small-scale resource providers, for a complex system in the conditions of dynamic computing resources and fierce competition in obtaining resources, they cannot develop and adaptively manage the conditions optimally. To optimize the resource allocation with minimal delay, low energy consumption, minimum computational complexity, high scalability, and better resource utilization efficiency, CC/FC/EC/IoT-based computing architectures should be designed intelligently. Therefore, the objective of this research is a comprehensive survey on resource allocation problems using computational intelligence-based evolutionary optimization and mathematical game theory approaches in different computing environments according to the latest scientific research achievements.
Related Concept Videos
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Ampere-Maxwell's Law: Problem-Solving
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
Limits to Natural Selection
Conservation of Energy: Application
Maxwell-Boltzmann Distribution: Problem Solving
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Distributed Loads: Problem Solving

