Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms
Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms
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DOI：
10.1057/palgrave.jors.2601563
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发表时间：
2003-06
影响因子：
3.6
通讯作者：
Javier Alcaraz;Concepción Maroto;Rubén Ruiz
中科院分区：
文献类型：
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作者：
Javier Alcaraz;Concepción Maroto;Rubén Ruiz
本文研究了以最大完工时间最小化为目标的多模式资源约束项目调度问题。我们开发了新的遗传算法，扩展了以前为单模问题设计的表示和运算符。此外，对于不可行的个体，我们定义了一个新的适应度函数。我们已经测试了该算法的不同变体，并使用PSPLIB中包含的标准实例集，选择了最好的算法与之前发布的不同启发式算法进行比较。结果表明，该算法具有良好的性能。
In this paper we consider the Multi-Mode Resource-Constrained Project Scheduling Problem with makespan minimisation as the objective. We have developed new genetic algorithms, extending the representation and operators previously designed for the single-mode version of the problem. Moreover, we have defined a new fitness function for the individuals who are infeasible. We have tested different variants of the algorithm and chosen the best to be compared to different heuristics previously published, using standard sets of instances included in PSPLIB. Results illustrate the good performance of our algorithm.