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Comparative analysis of ant colony extended and mix-min ant system in software project scheduling problem

机译:软件项目调度问题中蚁群扩展和混合闽蚁系统的比较分析

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Software Project Scheduling Problem (SPSP) is one of Project Scheduling Problem which is classified as NP-Hard problem. In 2014, variation of Ant Colony Optimization (ACO) algorithms was successfully developed. The algorithm is Max-Min Ant System (MMAS) that proposed to solve SPSP. In 2012, there is variation of ACO named Ant Colony Extended (ACE) developed for Travelling Salesman Problem and it shows better performance than well-known ACO algorithms: MMAS and Ant Colony System (ACS). However, there is no research about ACE's performance in SPSP where MMAS is successfully applied. In this paper, ACE and MMAS algorithm were compared in SPSP. The experiment result shows that ACE has better performance than MMAS for SPSP. The performance is indicated by fitness value of the algorithms.
机译:软件项目调度问题(SPSP)是项目调度问题之一,被归类为NP-Colly问题。 2014年,成功开发了蚁群优化(ACO)算法的变化。该算法是建议解决SPSP的MAX-MIN ANT系统(MMAS)。 2012年,为旅行推销员问题开发的ACO命名蚁群的ACO变化,它显示出比着名的ACO算法:MMA和蚁群系统(ACS)更好的性能。但是,没有关于ACE在SPSP中表现的研究,其中MMAS已成功应用。在本文中,在SPSP中比较了ACE和MMAS算法。实验结果表明,ACE具有比SPSP的MMA更好的性能。性能由算法的适应值表示。

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