基于信息素矩阵优化蚁群算法求解城市建模的旅行商问题
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Travelling salesman of urban modeling based on pheromone matrix optimization ant colony algorithm
Liu Daia，Zhang Yamingʰ，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
随着城市场景丰富和城市系统扩大，城市管理进人新阶段。（剩余20675字）