一种基于人工蜂群算法的多目标路径决策方法.docx

一种基于人工蜂群算法的多目标路径决策方法
摘要:
在多目标路径决策中，寻找最短路径和最优路径是一个非常重要的问题，这个问题已经被广泛研究。本文提出了一种基于人工蜂群算法的多目标路径决策方法。该方法实现了由多个目标函数组成的多目标构建路径的优化问题。最短路径和最短时间路径是最常见的目标函数，此外我们还可以将其他目标函数加入到算法中。实验结果表明，与其他算法相比，该算法能够产生更好的性能表现。
关键词：人工蜂群算法，多目标路径决策，优化问题，目标函数
Abstract:
Inmulti-objectivepathdecision,findingtheshortestpathandoptimalpathisaveryimportantproblemthathasbeenwidelyresearched.Inthispaper,amulti-objectivepathdecisionmethodbasedonartificialbeecolonyalgorithmisproposed.Themethodrealizestheoptimizationproblemofconstructingapathcomposedofmultipleobjectivefunctions.Theshortestpathandtheshortesttimepatharethemostcommonobjectivefunctions.Inaddition,wecanaddotherobjectivefunctionstothealgorithm.Theexperimentalresultsshowthatcomparedwithotheralgorithms,thealgorithmcanproducebetterperformance.
Keywords:ArtificialBeeColonyAlgorithm,multi-objectivepathdecision,optimizationproblem,objectivefunction
Introduction:
Pathdecisionisacriticalandchallengingtaskinmanyfieldsandareas,includingtransportation,supplychainmanagement,andnetworkoptimization.Findingtheshortestpathandoptimalpathisthemostcommonobjectiveofpathdecision.Multiplecriteriamaycomeintoconsiderationwhilemakingthepathdecision,suchasshortestpath,fastestpath,andthepathwiththeleastcost.
Artificialbeecolony(ABC)algorithmisametaheuristicoptimizationalgorithmthatmimicstheintelligentforagingbehaviorofhoneybees.ABCalgorithmhasbeenwidelyinvestigatedandappliedinavarietyofoptimizationproblems,suchasneuralnetworkoptimization,imageprocessing,anddataclustering.TheadvantagesofABCincluderapidconvergencecapability,simplicity,andlowcomputationrequirements.
Inthispaper,weproposeamulti-objectivepathdecisionmethodbasedonABCalgorithmthatcanoptimizethepathdecisionproblemwithmultiplecriteria.
Methodology:
Theproposedmethodinvolvesseveralsteps:
1.Encodingthepathdecisionproblem
Thepathdecisionproblemcanbeencodedasagraph,wherenodesrepresentvariouswaypointsorlocations,andedgesrepresentthepathsorconnectionsbetweenthem.Eachedgehasanassociatedweight,whichcanbethedistance,traveltime