CC-DHCR PLANNING AND SCHEDULING METHOD BASED ON SLAB CLUSTER

2008 ◽  
Vol 07 (02) ◽  
pp. 249-252 ◽  
Author(s):  
HELAN LIANG ◽  
SUJIAN LI
Keyword(s):  
Continuous Casting ◽  
Production Process ◽  
Dynamic Scheduling ◽  
New Method ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Scheduling Method

Focusing on the limitations of the traditional Continuous Casting-Direct Hot Charge Rolling (CC-DHCR) planning and scheduling methods that rarely consider dynamic scheduling problems, a new method is put forward. The key idea is to make out clusters and integrated plans in the planning layer, and then to adjust the rolling sequences according to the slab cluster-based strategy in the dynamic scheduling layer. Results of the test with data from practical production process show that the method can effectively solve the CC-DHCR planning and scheduling problem and increase the DHCR ratio.

Research of Flexible Dynamic Scheduling Problem Based on Genetic Algorithm

2009 ◽  
Vol 16-19 ◽  
pp. 743-747
Author(s):  
Yu Wu ◽  
Xin Cun Zhuang ◽  
Cong Xin Li
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Scheduling Problem ◽  
Static Scheduling ◽  
Coding Method ◽  
Scheduling Method ◽  
Distribution Principle ◽  
Working Procedure

Solve the flexible dynamic scheduling problem by using “dynamic management & static scheduling” method. Aim at the property of flexible Manufacturing systems, the dynamic scheduling methods are analyzed and a coding method based on working procedure is improved in this paper. Thus it can be efficiently solve the problem of multiple working routes selection under the active distribution principle. On the other hand, the self-adaptive gene is provided and the parameters of the genetic algorithm are defined. In such a solution, the scheduling is confirmed to be simple and efficient.

scholarly journals Production planning and scheduling problem of continuous parallel lines with demand uncertainty and different production capacities

2020 ◽  
Vol 7 (6) ◽  
pp. 761-774
Author(s):  
Kailash Changdeorao Bhosale ◽  
Padmakar Jagannath Pawar
Keyword(s):  
Production Planning ◽  
Demand Uncertainty ◽  
Clustering Algorithm ◽  
Real Life ◽  
Initial Population ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling

Abstract Production planning and scheduling problems are highly interdependent as scheduling provides optimum allocation of resources and planning is an optimum utilization of these allocated resources to serve multiple customers. Researchers have solved production planning and scheduling problems by the sequential method. But, in this case, the solution obtained by the production planning problem may not be feasible for scheduling method. Hence, production planning and scheduling problems must be solved simultaneously. Therefore, in this work, a mathematical model is developed to integrate production planning and scheduling problems. The solution to this integrated planning and scheduling problem is attempted by using a discrete artificial bee colony (DABC) algorithm. To speed up the DABC algorithm, a k-means clustering algorithm is used in the initial population generation phase. This k-means clustering algorithm will help to converge the algorithm in lesser time. A real-life case study of a soap manufacturing industry is presented to demonstrate the effectiveness of the proposed approach. An objective function to minimize overall cost, which comprises the processing cost, material cost, utility cost, and changeover cost, is considered. The results obtained by using DABC algorithm are compared with those obtained by CPLEX software. There is a saving of ₹2 23 324 for weeks 1–4 in overall cost compared with the results obtained by using CPLEX software.

scholarly journals Fitness Distance Correlation Strategy for Solving the RGV Dynamic Scheduling Problem

2020 ◽  
Vol 14 (3) ◽  
pp. 20-40
Author(s):  
Wei Li ◽  
Furong Tian ◽  
Ke Li
Keyword(s):  
Dynamic Scheduling ◽  
Programming Model ◽  
Operating Efficiency ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Distance Correlation ◽  
Fast Running ◽  
Stable Performance ◽  
Fitness Distance Correlation ◽  
Working Efficiency

Rail guide vehicle (RGV) problems have the characteristics of fast running, stable performance, and high automation. RGV dynamic scheduling has a great impact on the working efficiency of an entire automated warehouse. However, the relative intelligent optimization research of different workshop components for RGV dynamic scheduling problems are insufficient scheduling in the previous works. They appear idle when waiting, resulting in reduced operating efficiency during operation. This article proposes a new distance landscape strategy for the RGV dynamic scheduling problems. In order to solve the RGV dynamic scheduling problem more effectively, experiments are conducted based on the type of computer numerical controller (CNC) with two different procedures programming model in solving the RGV dynamic scheduling problems. The experiment results reveal that this new distance landscape strategy can provide promising results and solves the considered RGV dynamic scheduling problem effectively.

scholarly journals The Novel Heuristic for Data Transmission Dynamic Scheduling Problems

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Hao Xu ◽  
Yue Zhao ◽  
Li-Ning Xing ◽  
You Zhou
Keyword(s):  
Resource Utilization ◽  
Data Transmission ◽  
Dynamic Scheduling ◽  
Time Windows ◽  
Experimental Results ◽  
Scheduling Problem ◽  
The Novel ◽  
Scheduling Problems ◽  
Transmission Dynamic ◽  
Simple Rules

The data transmission dynamic scheduling is a process that allocates the ground stations and available time windows to the data transmission tasks dynamically for improving the resource utilization. A novel heuristic is proposed to solve the data transmission dynamic scheduling problem. The characteristic of this heuristic is the dynamic hybridization of simple rules. Experimental results suggest that the proposed algorithm is correct, feasible, and available. The dynamic hybridization of simple rules can largely improve the efficiency of scheduling.

Dynamic Scheduling Method for Steelmaking-Continuous Casting

2010 ◽  
Vol 44-47 ◽  
pp. 2162-2167 ◽  
Author(s):  
Dong Feng He ◽  
Ai Jun Xu ◽  
Gang Yu ◽  
Nai Yuan Tian
Keyword(s):  
Genetic Algorithm ◽  
Continuous Casting ◽  
Dynamic Scheduling ◽  
Utilization Rate ◽  
Production Data ◽  
High Quality ◽  
Static Scheduling ◽  
Scheduling Method ◽  
Scheduling Plan ◽  
Generation Period

A method of dynamic scheduling of steelmaking-continuous casting is proposed, which includes static scheduling based on genetic algorithm and dynamic scheduling based on scheduling rules, mathematical model and complete rescheduling utilizing genetic algorithm. The simulation with eight hours’ production data in S steel plant showed that the method could draw quickly a high quality and performable dynamic scheduling plan according to random production disturbance. The average utilization rate of converter could reach 95% and the generation period of initial scheduling is less than 3 minutes. The max dynamic scheduling adjustment period did not exceed 1 minute.

A Heuristic Algorithm for Flowshop Scheduling Problem

2012 ◽  
Vol 591-593 ◽  
pp. 626-630
Author(s):  
Dan Tang ◽  
Hong Ping Shu
Keyword(s):  
Heuristic Algorithm ◽  
Flow Shop ◽  
New Method ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Work Shop ◽  
And Performance ◽  
Flowshop Scheduling Problem ◽  
Better Than

Flow Shop Scheduling Problem is a class of scheduling problems with a work shop in which the flow control shall enable an appropriate sequencing for each job and for processing on a set of machines in compliance with given processing orders. In this paper, we propose a new heuristic algorithm based on the analysis and research of which problem, the new method introducing a evaluate mechanism of the relative position of any two jobs to the completion time, and the efficiency and performance has been improved .The result of simulation experiments shows that, our new heuristic algorithm has good performance, and the average quality and stability of scheduling sequences generated by new method is significantly better than other heuristic algorithm which has the same complexity.

scholarly journals Energy efficiency, robustness, and makespan optimality in job-shop scheduling problems

2015 ◽  
Vol 30 (3) ◽  
pp. 300-312 ◽  
Author(s):  
Miguel A. Salido ◽  
Joan Escamilla ◽  
Federico Barber ◽  
Adriana Giret ◽  
Dunbing Tang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Production Scheduling ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Efficient Solutions ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Job Shop Scheduling Problem ◽  
Planning And Scheduling ◽  
Shop Scheduling

AbstractMany real-world problems are known as planning and scheduling problems, where resources must be allocated so as to optimize overall performance objectives. The traditional scheduling models consider performance indicators such as processing time, cost, and quality as optimization objectives. However, most of them do not take into account energy consumption and robustness. We focus our attention in a job-shop scheduling problem where machines can work at different speeds. It represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The main goal of the paper is focused on the analysis of three important objectives (energy efficiency, robustness, and makespan) and the relationship among them. We present some analytical formulas to estimate the ratio/relationship between these parameters. It can be observed that there exists a clear relationship between robustness and energy efficiency and a clear trade-off between robustness/energy efficiency and makespan. It represents an advance in the state of the art of production scheduling, so obtaining energy-efficient solutions also supposes obtaining robust solutions, and vice versa.

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