Biased random-key genetic algorithms for the weighted minimum broadcast time problem

IF 4.5 3区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Alfredo Lima, Luiz Satoru Ochi, Bruno Nogueira, Rian G. S. Pinheiro
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引用次数: 0

Abstract

Broadcasting is an essential operation in distributed systems, with a wide range of applications. This study is focused on solving the Weighted Minimum Broadcast Time (WMBT), a problem that extends the classical Minimum Broadcast Time problem (MBT) by incorporating costs associated with each communication operation. We propose five contributions to the WMBT: (i) an integer linear programming model, (ii) two greedy algorithms, (iii) two Biased Random-Key Genetic Algorithms (BRKGAs), (iv) a lower bound algorithm, (v) a reduction rule to decrease an instance size, and (vi) a method to create instances with known optimal solutions. Our novel approaches are compared with state-of-the-art methods using large-scale synthetic instances. The experimental results demonstrate the effectiveness of our proposals. The greedy algorithms attains the best known solutions in a significant number of instances, while the two BRKGAs further enhance this performance, surpassing the greedy algorithms in many of the tested instances.

Abstract Image

加权最小广播时间问题的有偏随机密钥遗传算法
广播是分布式系统中必不可少的操作,有着广泛的应用。本研究的重点是解决加权最小广播时间(WMBT)问题,该问题通过纳入与每次通信操作相关的成本,扩展了经典的最小广播时间问题(MBT)。我们提出了对WMBT的五个贡献:(i)整数线性规划模型,(ii)两个贪婪算法,(iii)两个有偏差的随机密钥遗传算法(BRKGAs), (iv)下界算法,(v)减少实例大小的约简规则,以及(vi)创建具有已知最优解的实例的方法。我们的新方法与使用大规模合成实例的最先进方法进行了比较。实验结果证明了所提方法的有效性。贪婪算法在相当数量的实例中获得了最知名的解决方案,而两个BRKGAs进一步提高了这种性能,在许多测试实例中超过了贪婪算法。
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来源期刊
Annals of Operations Research
Annals of Operations Research 管理科学-运筹学与管理科学
CiteScore
7.90
自引率
16.70%
发文量
596
审稿时长
8.4 months
期刊介绍: The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications. In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.
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