A Forager Adjustment Strategy Used by the Bees Algorithm for Solving Optimization Problems in Cloud Manufacturing

Yongquan Xie, Zude Zhou, Quan Liu, Wenjun Xu, Chunqian Ji, Ping Liu, Sisi Tian, Duc Pham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Intelligent technologies have become increasingly important in manufacturing nowadays. Optimal service management and allocation in current cloud manufacturing model are impossible without applications of appropriate intelligent tools. The Bees Algorithm (BA) is a swarm-based intelligent optimizer that provides support for smart decision-making process in manufacturing models. A novel forager adjustment strategy (FAS) is proposed in this paper to manage the forager division in the algorithm, so as to make the entire colony perform with higher efficiency. The proposed FAS based Bees Algorithm (FAS-BA) is able to realize flexible allocation of its forager resources between different roles in accordance with the solution fitness sampled by current scout population. The proposed algorithm is presented in detail. Experiments are conducted based on a set of well-known benchmark functions and a case study. Comparisons between FAS-BA and an improved Bees Algorithm are made to highlight the effectiveness of FAS. The results demonstrate that the proposed algorithm requires less function evaluation cost than the improved version but is capable of obtaining at least the same optimal solution to a problem.
Original languageEnglish
Title of host publicationProceedings ASME 2015 International Manufacturing Science and Engineering Conference
Subtitle of host publicationVolume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing
PublisherASME (American Society of Mechanical Engineers)
ISBN (Print)978-0-7918-5682-6
Publication statusPublished - 2015
Event10th ASME 2015 Manufacturing Science and Engineering Conference (MSEC2015) - Charlotte, NC, United States
Duration: 8 Jun 201512 Jun 2015


Conference10th ASME 2015 Manufacturing Science and Engineering Conference (MSEC2015)
Country/TerritoryUnited States
CityCharlotte, NC


  • Swarm intelligence
  • Bees Algorithm
  • Forager adjustment strategy
  • Intelligent optimization
  • Cloud manufacturing


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