Lagrangian relaxation with cut generation for hybrid flowshop scheduling problems to minimize the total weighted tardiness

2010 ◽  
Vol 37 (1) ◽  
pp. 189-198 ◽  
Author(s):  
Tatsushi Nishi ◽  
Yuichiro Hiranaka ◽  
Masahiro Inuiguchi
Keyword(s):  
Lagrangian Relaxation ◽  
Total Weighted Tardiness ◽  
Scheduling Problems ◽  
Flowshop Scheduling ◽  
Hybrid Flowshop ◽  
Weighted Tardiness ◽  
Hybrid Flowshop Scheduling ◽  
Cut Generation

Hybrid Flowshop Scheduling with Finite Transportation Capacity

2011 ◽  
Vol 65 ◽  
pp. 574-578 ◽  
Author(s):  
Hua Xuan
Keyword(s):  
Lagrangian Relaxation ◽  
Programming Model ◽  
Optimal Schedule ◽  
Release Time ◽  
Flowshop Scheduling ◽  
Hybrid Flowshop ◽  
Relaxation Algorithm ◽  
Hybrid Flowshop Scheduling ◽  
Transportation Capacity ◽  
Lagrangian Relaxation Algorithm

This paper studies a class of hybrid flowshop scheduling problem characterized by release time, transportation time and transportation capacity of one unit for each transporter. This problem is formulated as an integer programming model and a Lagrangian relaxation algorithm is designed to solve it. Testing results on problems of small to medium sizes show that the Lagrangian relaxation algorithm can obtain an acceptable near optimal schedule within a shorter CPU time.

scholarly journals A Discrete Group Search Optimizer for Hybrid Flowshop Scheduling Problem with Random Breakdown

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Zhe Cui ◽  
Xingsheng Gu
Keyword(s):  
Discrete Group ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Flowshop Scheduling ◽  
Hybrid Flowshop ◽  
Random Breakdown ◽  
Hybrid Flowshop Scheduling ◽  
Discrete Operators ◽  
Flowshop Scheduling Problem ◽  
Group Search

The scheduling problems have been discussed in the literature extensively under the assumption that the machines are permanently available without any breakdown. However, in the real manufacturing environments, the machines could be unavailable inevitably for many reasons. In this paper, the authors introduce the hybrid flowshop scheduling problem with random breakdown (RBHFS) together with a discrete group search optimizer algorithm (DGSO). In particular, two different working cases, preempt-resume case, and preempt-repeat case are considered under random breakdown. The proposed DGSO algorithm adopts the vector representation and several discrete operators, such as insert, swap, differential evolution, destruction, and construction in the producers, scroungers, and rangers phases. In addition, an orthogonal test is applied to configure the adjustable parameters in the DGSO algorithm. The computational results in both cases indicate that the proposed algorithm significantly improves the performances compared with other high performing algorithms in the literature.

scholarly journals Solving Distributed Hybrid Flowshop Scheduling Problems by a Hybrid Brain Storm Optimization Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 66879-66894 ◽  
Author(s):  
Jian-Hua Hao ◽  
Jun-Qing Li ◽  
Yu Du ◽  
Mei-Xian Song ◽  
Peng Duan ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Scheduling Problems ◽  
Flowshop Scheduling ◽  
Hybrid Flowshop ◽  
Hybrid Flowshop Scheduling ◽  
Brain Storm Optimization
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