scholarly journals Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021 ◽  
Vol 28 (2) ◽  
2020 ◽  
Vol 19 (4) ◽  
pp. 559-570
Author(s):  
D. Istokovic ◽  
M. Perinic ◽  
M. Vlatkovic ◽  
M. Brezocnik

To ensure the competitiveness of manufacturing companies in the market, batching and batch scheduling are among the most important tasks. This paper presents a simulation-optimization approach that combines the discrete event simulation (DES) and the genetic algorithm (GA) to solve the batching and batch scheduling problem in a hybrid flow shop (HFS). HFS is widely used for the production of medium and large quantities of different technologically complex products. Based on a real-world manufacturing company, the HFS simulation model was developed using the Tecnomatix Plant Simulation software package. By analysing the influencing factors that represent production costs, a new formulation of the total cost of production was proposed. The purpose of this case study was to ensure timely delivery and minimize production costs by integrating simulation and optimization tools. This research considers sequence-dependent setup times, and availability of manufacturing and transportation equipment. The results of this research showed that the proposed simulation-optimization approach can be applied to solve the problem in many industrial case studies.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223782-223796
Author(s):  
Xixing Li ◽  
Hongtao Tang ◽  
Zhipeng Yang ◽  
Rui Wu ◽  
Yabo Luo

2014 ◽  
Vol 77 (1-4) ◽  
pp. 751-761 ◽  
Author(s):  
A. Azadeh ◽  
B. Maleki-Shoja ◽  
M. Sheikhalishahi ◽  
A. Esmaili ◽  
A. Ziaeifar ◽  
...  

Author(s):  
Amos H.C. Ng ◽  
Jacob Bernedixen ◽  
Martin Andersson ◽  
Sunith Bandaru ◽  
Thomas Lezama

Author(s):  
Jingcao Cai ◽  
Deming Lei

AbstractDistributed hybrid flow shop scheduling problem (DHFSP) has attracted some attention; however, DHFSP with uncertainty and energy-related element is seldom studied. In this paper, distributed energy-efficient hybrid flow shop scheduling problem (DEHFSP) with fuzzy processing time is considered and a cooperated shuffled frog-leaping algorithm (CSFLA) is presented to optimize fuzzy makespan, total agreement index and fuzzy total energy consumption simultaneously. Iterated greedy, variable neighborhood search and global search are designed using problem-related features; memeplex evaluation based on three quality indices is presented, an effective cooperation process between the best memeplex and the worst memeplex is developed according to evaluation results and performed by exchanging search times and search ability, and an adaptive population shuffling is adopted to improve search efficiency. Extensive experiments are conducted and the computational results validate that CSFLA has promising advantages on solving the considered DEHFSP.


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