A two-stage iterated greedy algorithm for distributed blocking flowshop scheduling problem

This paper deals with the distributed blocking flowshop scheduling problem (DBFSP), a critical challenge in modern manufacturing systems involving multiple factories. Each factory operates as a blocking flowshop without intermediate buffers between successive machines. The objective of DBFSP is to m...

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Bibliographic Details
Published in:Expert systems with applications Vol. 300; p. 130422
Main Authors: Zhang, Sen, Qian, Bin, Hu, Rong, Li, Kun, Yang, Jian-Bo
Format: Journal Article
Language:English
Published: Elsevier Ltd 05.03.2026
Subjects:
Distributed blocking flowshop
Iterated greedy algorithm
Local search
Makespan
Scheduling
Distributed blocking flowshop
Local search
Iterated greedy algorithm
Makespan
Scheduling
ISSN:0957-4174
Online Access:Get full text
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Summary:This paper deals with the distributed blocking flowshop scheduling problem (DBFSP), a critical challenge in modern manufacturing systems involving multiple factories. Each factory operates as a blocking flowshop without intermediate buffers between successive machines. The objective of DBFSP is to minimize the makespan among all factories. First, a mixed integer linear programming model (MILP) is presented based on the positions of jobs. Second, by analyzing problem-specific properties, we prove two theorems: (1) removing a job from a factory reduces the factory’s makespan, and (2) inserting a new job into a factory increases the factory’s makespan. Then, an effective two-stage iterated greedy (TIG) algorithm is proposed. TIG includes a constructive heuristic method, a local search procedure with a multi-neighborhood structure designed according to the above two theorems, and a novel destruction and construction combining the total blocking time and idle time of each job. Finally, results of experiments on 720 benchmark instances demonstrate that the proposed TIG algorithm outperforms state-of-the-art DBFSP methods. In addition, 320 out of 720 instances achieve new best-known solutions with significant margins.
ISSN:0957-4174
DOI:10.1016/j.eswa.2025.130422