论文标题
PACO的加权人口更新规则适用于单机器总加权问题
A Weighted Population Update Rule for PACO Applied to the Single Machine Total Weighted Tardiness Problem
论文作者
论文摘要
在本文中，提出了针对基于人群的蚂蚁菌落优化（PACO）的新人口更新规则。 PACO是标准蚂蚁菌落优化算法的众所周知的替代方法。新的更新规则允许加权解决方案的不同部分。与新更新规则的PACO有关单机器总加权问题（SMTWTP）的示例进行评估。这是一个$ \ Mathcal {np} $ - 硬优化问题，其目的是安排单台计算机上的作业，以便将其总加权拖延最小化。具有新的人口更新规则的PACO通过托管的几个基准实例进行了评估。此外，通过实验分析了工作权重对人群解决方案和算法收敛性的影响。结果表明，具有新更新规则的PACO平均具有比PACO具有标准更新规则更好的解决方案质量。
In this paper a new population update rule for population based ant colony optimization (PACO) is proposed. PACO is a well known alternative to the standard ant colony optimization algorithm. The new update rule allows to weight different parts of the solutions. PACO with the new update rule is evaluated for the example of the single machine total weighted tardiness problem (SMTWTP). This is an $\mathcal{NP}$-hard optimization problem where the aim is to schedule jobs on a single machine such that their total weighted tardiness is minimized. PACO with the new population update rule is evaluated with several benchmark instances from the OR-Library. Moreover, the impact of the weights of the jobs on the solutions in the population and on the convergence of the algorithm are analyzed experimentally. The results show that PACO with the new update rule has on average better solution quality than PACO with the standard update rule.
