arrow
Return

Effective constructive heuristic and iterated greedy algorithm for distributed mixed blocking permutation flow-shop scheduling problem

delete2021-06-01
delete35
PRE
AI
邵仲世 cover
邵仲世 (Zhongshi Shao)
W
Weishi Shao *
皮
皮德常 (Dechang Pi)
DOI:10.1016/j.knosys.2021.106959delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Distributed permutation flow-shop scheduling problem (DPFSP) has achieved much attention in recent years, which always assumes that there are infinite buffers between any consecutive machines. However, in many practical industrials, no buffers exist between some consecutive machines due to space constraint or technological requirement, which generate various types of blocking constraint. Hence, a distributed mixed permutation blocking flow-shop scheduling problem (DMBPFSP) is investigated in this paper, which considers three types of blocking constraint and without blocking. The objective is to minimize the maximum makespan among all factories. To address this problem, an improved NEH heuristic (NEH_P) is proposed, which incorporates the re-optimization of partial solutions. Afterwards, an efficient iterated greedy (EIG) algorithm is proposed. In the proposed EIG, the NEH_P heuristic is employed to generate the initial solution with high quality. A problem-specific knowledge based destruction-construction is used to explore the solution space. Three efficient local search procedures are designed to implement exploitation around the critical factory and exploitation across multi factory. We compare the proposed methods against the closely relevant and high-performing methods in the literature. The computational results indicate that both NEH_P and EIG are very effective for addressing the considered problem. (c) 2021 Elsevier B.V. All rights reserved.
Keywords:
Distributed manufacturing
Flow-shop scheduling
Blocking constraints
Constructive heuristic
Iterated greedy method
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.3W
Citations:
4.5W

Organization

S
Shaanxi Normal University
Scholars:
1.6W
Papers: 1.1W
Citations: 1.7W
N
Nanjing Normal University
Scholars:
1.7W
Papers: 1.3W
Citations: 1.9W
Cited Papers

Cited Papers

Feeding Response to Mercaptoacetate in Osborne‐Mendel and S5B/PL Rats
err2012-09-06
err0
errOAAI
errLori K. Singer; David A. York; George A. Bray
errShare
errSave
errShare
errSave
A Three-Stage Multiobjective Approach Based on Decomposition for an Energy-Efficient Hybrid Flow Shop Scheduling Problem
err2020-12-01
err110
PREAI
errZhang, Biao; Pan, Quan-Ke; Gao, Liang; Meng, Lei-Lei; Li, Xin-Yu; Peng, Kun-Kun
errShare
errSave
Variable neighbourhood search: methods and applications
err2009-10-28
err643
PREAI
errHansen, Pierre; Mladenovic, Nenad; Moreno Perez, Jose A.
errShare
errSave
errShare
errSave
researcher View more