基于信息素矩陣優(yōu)化蟻群算法求解城市建模的旅行商問題
Travelling salesman of urban modeling based on pheromone matrix optimization ant colony algorithm
Liu Daia,Zhang Yaming?,Wang Kaib,Cui Haiqingh? (a.EngineegnCteFlfocftoutoatoltionUsitof 300000,China)
Abstract:This paper proposedanoptimizedantcolonyalgorithm toaddressthe traveling salesman problem(TSP)inurban modeling.Thealgorithmintegratedrandomaveragingofthepheromone matrix,adaptiveperturbation,anddynamicproportional resetingstrategies tooptimizethepath search intheprocessof acquiringurban modeling materials.Aftereachroundof path selection,thealgorithmgloballyupdatedthelocalpheromonebasedonthequalityof thepathsandacceleratedconvergence through2-optoptimization.Initialy,itappliedtherandomaveraging strategy.When theoptimalpathhadnotbeenupdated formultiple iterations,thepheromoneofrandom nodes wasaveraged toavoidlocaloptima.Whenmultipleatemptsattherandomaveraging strategyproveinefective,itintroducedtheadaptiveperturbationstrategy.Thisstrategyperturbedtheperomone matrix toselectpaths,therebyreducing theriskoflocal optima.This strategyperturbedthepheromonematrix toselect paths,reducingtheriskoflocaloptima.Whenthequalityof theoptimalpathdecreases byacertain proportion,itusedthe dynamicproportionalresetingstrategytoincreasethediferencebetweenhighandlowpheromonevaluesinthematrix,further accelerating convergence.Theresultsshowthatthealgorithm efectivelyimprovesglobal search capability,acelerates the convergence process,and provides a solution to the TSP in urban modeling.
Key words:antcolonyalgorithm;traveler’ssalesmanproblem;combinatorial optimization;2-optalgorithm;urban 3D modeling
0 引言
隨著城市場(chǎng)景豐富和城市系統(tǒng)擴(kuò)大,城市管理進(jìn)人新階段。(剩余20675字)
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- 計(jì)算機(jī)應(yīng)用研究
- 2025年06期
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