Efficient Lagrangian heuristics for the two-stage flow shop with job dependent buffer requirements

2018 ◽  
Vol 52-53 ◽  
pp. 143-155 ◽  
Author(s):  
Hanyu Gu ◽  
Alexander Kononov ◽  
Julia Memar ◽  
Yakov Zinder
2011 ◽  
Vol 268-270 ◽  
pp. 476-481
Author(s):  
Li Gao ◽  
Ke Lin Xu ◽  
Wei Zhu ◽  
Na Na Yang

A mathematical model was constructed with two objectives. A two-stage hybrid algorithm was developed for solving this problem. At first, the man-hour optimization based on genetic algorithm and dynamic programming method, the model decomposes the flow shop into two layers: sub-layer and patrilineal layer. On the basis of the man-hour optimization,A simulated annealing genetic algorithm was proposed to optimize the sequence of operations. A new selection procedure was proposed and hybrid crossover operators and mutation operators were adopted. A benchmark problem solving result indicates that the proposed algorithm is effective.


2014 ◽  
Vol 39 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Enrique Gerstl ◽  
Gur Mosheiov ◽  
Assaf Sarig

Abstract We study a special two-stage flexible flowshop, which consists of several parallel identical machines in the first stage and a single machine in the second stage. We assume identical jobs, and the option of batching, with a required setup time prior to the processing of a new batch. We also consider the option to use only a subset of the available machines. The objective is minimum makespan. A unique optimal solution is introduced, containing the optimal number of machines to be used, the sequence of batch sizes, and the batch schedule. The running time of our proposed solution algorithm is independent of the number of jobs, and linear in the number of machines


2013 ◽  
Vol 651 ◽  
pp. 548-552
Author(s):  
Parinya Kaweegitbundit

This paper considers two stage hybrid flow shop (HFS) with identical parallel machine. The objectives is to determine makespan have been minimized. This paper presented memetic algorithm procedure to solve two stage HFS problems. To evaluated performance of propose method, the results have been compared with two meta-heuristic, genetic algorithm, simulated annealing. The experimental results show that propose method is more effective and efficient than genetic algorithm and simulated annealing to solve two stage HFS scheduling problems.


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