A Study on Lead Time Prediction in Hybrid Flow-shop with Machine Failure through Simulation

2021 ◽  
Vol 26 (4) ◽  
pp. 324-332
Author(s):  
So-Hui Park ◽  
Jun-Woo Kim
Keyword(s):  
Lead Time ◽  
Flow Shop ◽  
Hybrid Flow Shop ◽  
Time Prediction ◽  
Machine Failure

scholarly journals Lead time prediction in a flow-shop environment with analytical and machine learning approaches

2018 ◽  
Vol 51 (11) ◽  
pp. 1029-1034 ◽  
Author(s):  
Dávid Gyulai ◽  
András Pfeiffer ◽  
Gábor Nick ◽  
Viola Gallina ◽  
Wilfried Sihn ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lead Time ◽  
Flow Shop ◽  
Learning Approaches ◽  
Time Prediction

scholarly journals A cooperated shuffled frog-leaping algorithm for distributed energy-efficient hybrid flow shop scheduling with fuzzy processing time

2021 ◽  
Author(s):  
Jingcao Cai ◽  
Deming Lei
Keyword(s):  
Energy Efficient ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Distributed Energy ◽  
Shuffled Frog Leaping Algorithm ◽  
Shop Scheduling ◽  
Fuzzy Processing Time ◽  
Hybrid Flow Shop Scheduling ◽  
Shuffled Frog Leaping

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.

scholarly journals Prototyping Machine-Learning-Supported Lead Time Prediction Using AutoML

2021 ◽  
Vol 180 ◽  
pp. 649-655
Author(s):  
Janek Bender ◽  
Jivka Ovtcharova
Keyword(s):  
Machine Learning ◽  
Lead Time ◽  
Time Prediction

scholarly journals Integrated Optimization Approach of Hybrid Flow-Shop Scheduling Based on Process Set

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223782-223796
Author(s):  
Xixing Li ◽  
Hongtao Tang ◽  
Zhipeng Yang ◽  
Rui Wu ◽  
Yabo Luo
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Optimization Approach ◽  
Shop Scheduling ◽  
Integrated Optimization ◽  
Hybrid Flow Shop Scheduling

Memetic Algorithm Approach to Two-Stage Hybrid Flow Shop Scheduling Problem with Identical Parallel Machines

2013 ◽  
Vol 651 ◽  
pp. 548-552
Author(s):  
Parinya Kaweegitbundit
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Parallel Machines ◽  
Flow Shop ◽  
Memetic Algorithm ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problems ◽  
Two Stage ◽  
Hybrid Flow Shop Scheduling

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.

Research on a Main-Branch Hybrid Flow Shop Scheduling Problem in Production Manufacturing System

2012 ◽  
Vol 252 ◽  
pp. 354-359
Author(s):  
Xin Min Zhang ◽  
Meng Yue Zhang
Keyword(s):  
Manufacturing System ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Quantum Genetic Algorithm ◽  
Shop Scheduling ◽  
Scheduling Model ◽  
Hybrid Flow Shop Scheduling ◽  
Two Stages

A main-branch hybrid Flow shop scheduling problem in production manufacturing system is studied. Under the premise of JIT, targeting of smallest cost, a Flow-Shop production line scheduling model is built in cycle time of buffer. Two stages Quantum Genetic Algorithm (QGA) is proposed. By the results of numerical example, the effective and advantageous of QGA was shown.

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