摘要
多目标资源受限项目调度问题普遍存在于生产经营活动中,具有较高的实用价值。本文提出了一种改进的多种群遗传算法以解决多目标资源受限项目调度问题,为改变现有算法计算步骤理解困难、不易推广的特点,巧妙地通过平移工作解决此类问题,算法首先对工作的优先级进行随机编码,然后根据工序约束进行解码,并根据解码结果安排工作调度,同时为防止无效迭代,融合了禁忌搜索的思想。最后,通过PSPLIB标准算例库中算例进行实验,实验结果表明该算法在具备较高精度的同时,兼顾了快捷性和简洁性。
The scenarios of different work competing for resources are not rare during the rapid development of enterprises.This has led to investigations on the problem of how can an optimum allocation of resources be achieved for a project subjected to limited resources.This study focused on the optimum resource allocation for those projects with limited resources but multiple objectives.In previous studies,the quality of solutions was often improved by increasing the algorithm′s complexity,which resulted in a lack of simplicity and long-period calculations.In this study,an improved multi-population genetic algorithm was proposed,and its performance has been evaluated against the standard algorithm in the literature.The results showed that the proposed algorithm yielded high-quality solutions and was more concise and efficient than the standard algorithm.Hence,the practical application of the proposed algorithm is recommended.A problem was first defined,and then a mathematical model was proposed.Two objectives of the shortest construction period and optimum resource allocation were defined for the project.Since the two objectives could conflict,priority was given to the minimum construction period.In other words,an optimum resource allocation shall be achieved under the condition that the shortest construction period is guaranteed.This study combined two models of the“peak cutting and valley filling”and“minimum variance”and established a model for calculating the equilibrium degree of resource allocation.The larger value of the solution indicates a more balanced resource allocation.Then,the established model was optimized based on a prototype of the multi-population genetic algorithm.The procedure of the optimization is introduced as follows.First,the method for calculating the construction period under a specific code was modified to improve the calculation rate.A random code was first generated,and then the decoding process was arranged as per the work sequence.Afterwards,the shortest construction period was c
作者
薛松
陈旭
汪玉亭
丰景春
XUE Song;CHEN Xu;WANG Yuting;FENG Jingchun(Business School,Hohai University,Nanjing 211100,China;Jiangsu Provincial Collaborative Innovation Center of World Water Valley and Water Ecological Civilization,Nanjing 211100,China;Institute of Project Management,Hohai University,Nanjing 211100,China;Huzhou Institute of Smart City CO.,Ltd,Huzhou 313000,China)
出处
《管理工程学报》
CSSCI
CSCD
北大核心
2023年第5期167-175,共9页
Journal of Industrial Engineering and Engineering Management
基金
国家社会科学基金青年项目(15CJL023)
中央高校基本科研业务费专项资金资助项目(2019B19614)。
关键词
多目标优化
资源受限项目
项目调度问题
多种群遗传算法
Multi-objective optimization
Resource-constrained project
Project scheduling problem
MPGA
