Minimizing Makespan in Distributed Blocking Flowshops Using Hybrid Iterated Greedy Algorithms | Zendy

Kuo-Ching Ying | Zendy; Shih-Wei Lin | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Minimizing Makespan in Distributed Blocking Flowshops Using Hybrid Iterated Greedy Algorithms

Author(s) -

Kuo-Ching Ying,

Shih-Wei Lin

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2732738

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper studies the distributed blocking flow shop scheduling problem (DBFSP) using metaheuristics. A mixed integer programming model for solving the problem is proposed, and then three versions of the hybrid iterated greedy algorithm (HIG₁, HIG₂, and HIG₃) are developed, combining the advantages of an iterated greedy algorithm with the operators of the variable Tabu list, the constant Tabu list, and the cooling schedule. A benchmark problem set is used to assess empirically the performance of the HIG₁, HIG₂, and HIG₃ algorithms. Computational results show that all the three versions of the proposed algorithm can efficiently and effectively minimize the maximum completion time among all factories of the DBFSP, and HIG₁ is the most effective.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research