Chimpanzee Optimization Algorithm Task Scheduling Halton Sequence
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Solution Overview
Problem
Traditional chimpanzee optimization algorithms face issues with premature convergence and imbalance between global exploration and local exploitation, leading to local optimum solutions in task scheduling for cloud computing environments.
Innovation Solution
An improved chimpanzee optimization algorithm utilizing a two-dimensional Halton sequence for population initialization and a sine-cosine optimization strategy to enhance distribution and convergence, ensuring balanced global exploration and local exploitation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional chimpanzee optimization algorithm is used for task scheduling, then the algorithm is simple to implement with fewer control parameters, but the algorithm falls into local optimum and suffers from imbalance between global exploration and local exploitation
Solution Approach 1:
The patent introduces a two-dimensional function Halton sequence to generate pseudo-random numbers for population initialization, replacing traditional random initialization. This parameter change in the initialization method improves population distribution and diversity, enabling the algorithm to escape local optima while maintaining implementation simplicity
Solution Approach 2:
The patent transforms the traditional one-dimensional random initialization into a two-dimensional function Halton sequence initialization. This dimensional change creates a more uniform and diverse population distribution across the solution space, enhancing both global exploration and local exploitation capabilities
2Ease of manufacture
If traditional random initialization is used in chimpanzee algorithm, then the implementation is simple, but the population distribution is uneven leading to slow convergence
Solution Approach 1:
The patent changes the initialization parameter generation method from traditional random numbers to two-dimensional function Halton sequence. This parameter change ensures uniform population distribution across the solution space, significantly improving convergence speed while maintaining reasonable implementation complexity
Solution Approach 2:
The patent elevates the initialization process from one-dimensional random sampling to two-dimensional function-based Halton sequence generation. This dimensional enhancement creates superior population distribution patterns that accelerate convergence without substantially increasing implementation difficulty
3Adaptability or versatility
If chimpanzees release nature due to sexual motivation in late stage, then individual behavior is realistic, but the algorithm falls into local optimum and iteration stagnation occurs
Solution Approach 1:
The patent dynamically adjusts the sexual motivation parameter throughout the iteration process. By making this parameter time-dependent and adaptive, the algorithm maintains behavioral realism in different stages while preventing late-stage stagnation and ensuring continued convergence toward global optima
Data Source
AI summary
The present application discloses a task scheduling method based on an improved chimpanzee optimization algorithm, including obtaining a task to be scheduled and a task scheduling model pre-established by using a chimpanzee optimization algorithm, performing iterative computation of chimpanzees in the task scheduling model by the chimpanzee optimization algorithm; and ending the iterative computation in response to that an iteration termination condition is reached, outputting an optimal solution, and obtaining an optimal scheduling scheme. The present application solves the problem of the traditional chimpanzee optimization algorithm in the prior art that is prone to falling into the local optimum, and the imbalance between the global exploration capacity and the local exploitation capacity, the improved chimpanzee optimization algorithm has different aspects of performance enhancement compared to general intelligence algorithms of population.