A pipeline layout optimization method based on improved distance strategy imperialist algorithm

Abstract

A method for optimize pipeline layout based on an improved distance strategy imperialist algorithm comprise that following steps: respectively establishing three objective function of pipeline length,elbow number and installation convenience, and integrating obstacle avoidance constraint functions into three objective functions by using a penalty function method; Initializing the population, i.e.The country, calculating the objective function value of each country, constraining the total value of the violation and the state variables corresponding to the control variables, and copying the initial population to the external storage space; The algorithm iterates, adopts the improved distance strategy imperialist algorithm to optimize and update the country, copies the updated country to the external storage space and calculates the non-inferior ranking and congestion distance with the previous generation of countries, and then cuts according to the ranking to keep the size of the external storage space unchanged; According to the genetic algorithm, the optimal compromise solution is found from the Pareto optimal solution set, and the design is carried out according to the optimal compromise solution.

Description

technical field [0001] The invention belongs to the field of pipeline multi-objective layout optimization, in particular to a pipeline layout optimization method based on improved distance strategy imperialism algorithm. Background technique [0002] Complex equipment such as aeroengines usually contain a large number of pipelines and cables, and the requirements of multiple engineering rules need to be considered during the pipeline laying process. This problem is a typical multi-objective optimization problem. At present, pipeline laying generally only considers the construction period, quality, cost and other indicators, and uses the weighting method or variable weight weighting method to combine multiple objectives into one objective for optimization. The weight value used in this optimization method is subjective, and its optimal solution is just a simple superposition of multiple objective functions, which can only obtain a local optimal solution, and cannot provide de...

AI Technical Summary

Problems solved by technology

The algorithm has been successfully applied to a variety of optimization problems, which can verify the superiority of the algorithm in optimization problems, but the application in multi-objective problems is still very small, so the application of the imperialist algorithm in multi-objective problems and the algorithm's Improvement is worthy of in-depth study on the optimization method of pipeline layout

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