Product Processing Prioritization in Hybrid Flow Shop Systems Supported on Nash Bargaining Model and Simulation-Optimization

2021 ◽  
pp. 115066
Author(s):  
Hiva Malekpour ◽  
Ashkan Hafezalkotob ◽  
Kaveh Khalili-Damghani
Keyword(s):  
Flow Shop ◽  
Simulation Optimization ◽  
Nash Bargaining ◽  
Hybrid Flow Shop ◽  
Bargaining Model ◽  
Model And Simulation ◽  
Flow Shop Systems

scholarly journals Minimizing Total Production Cost in a Hybrid Flow Shop: a Simulation-Optimization Approach

2020 ◽  
Vol 19 (4) ◽  
pp. 559-570
Author(s):  
D. Istokovic ◽  
M. Perinic ◽  
M. Vlatkovic ◽  
M. Brezocnik
Keyword(s):  
Flow Shop ◽  
Simulation Optimization ◽  
Simulation Software ◽  
Production Costs ◽  
Batch Scheduling ◽  
Hybrid Flow Shop ◽  
Optimization Approach ◽  
Total Production ◽  
Manufacturing Companies ◽  
Dependent Setup Times

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.

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 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.

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