Job scheduling in virtual manufacturing cells with lot-streaming strategy: a new mathematical model formulation and a genetic algorithm approach

2012 ◽  
Vol 63 (5) ◽  
pp. 683-695 ◽  
Author(s):  
S E Kesen ◽  
Z Güngör
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Job Scheduling ◽  
Virtual Manufacturing ◽  
Model Formulation ◽  
Lot Streaming ◽  
Manufacturing Cells ◽  
Genetic Algorithm Approach ◽  
Virtual Manufacturing Cells

Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

2020 ◽  
pp. 095440542098068
Author(s):  
Kamran Forghani ◽  
S. M. T. Fatemi Ghomi ◽  
Reza Kia
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Model Material ◽  
Virtual Manufacturing ◽  
Superior Performance ◽  
Shop Floor ◽  
Processing Route ◽  
Manufacturing Cells ◽  
Comparison Results ◽  
Virtual Manufacturing Cells

Cell formation, scheduling, and facility layout are three main decisions in designing manufacturing cells. In this paper, we address the integration of these decisions in virtual manufacturing cells considering assembly aspects and process routing. We develop a mathematical model to determine the machine cells, the layout of machines and workstations on the shop floor, the processing route of parts, and the production sequence of operations on the machines. In this mathematical model, material handling costs and cycle time are minimized. To the best of our knowledge, this is the first paper that concurrently addresses the scheduling and layout of virtual manufacturing cells with assembly aspects and so-called criteria. To effectively solve the problem, a Population-based Simulated Annealing (PSA) combined with linear programming is proposed. The practical usability of the developed model is demonstrated in a case study. Finally, instances from the literature are solved to evaluate the performance of the PSA. The comparison results showed the superior performance of the PSA in comparison with CPLEX solver and standard simulated annealing.

A Petri Net and Genetic Algorithm Based Method for Flexible Manufacturing Cells Modeling and Scheduling

2009 ◽  
Vol 407-408 ◽  
pp. 268-272 ◽  
Author(s):  
Li Hong Qiao ◽  
Yi Xin Zhu ◽  
Jian Jun Yang ◽  
Yang Li
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Petri Net ◽  
Flexible Manufacturing ◽  
Simulated Annealing Algorithm ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Manufacturing Cells ◽  
Flexible Manufacturing Cells ◽  
Annealing Algorithm

The production organized in flexible manufacturing cells (FMC) can be a complicated issue when they are constrained by machines, robots, equipment and some other resources. Since machines and robots are the main bottleneck to the efficiency of FMC, this paper focused on the modeling and scheduling problem constrained by machines and robots. A common model representation, colored timed Petri net (CTPN) was utilized to build a FMC model constrained by robots and machines, which was then transformed to the simulation model. The scheduling problem was studied to establish a mathematical model of the FMC constrained by machines and robots. According to the model, a genetic algorithm was proposed to search an optimal solution by using an indirect coding of scheme. The effectiveness of the proposed algorithm was validated via an instance and the comparison with the result from the solution of simulated annealing algorithm.

Sign in / Sign up

Export Citation Format

Share Document