scholarly journals Optimizing model of a railroad yard’s operations plan based on production scheduling theory

2016 ◽  
Author(s):  
R. Guo ◽  
J. Guo ◽  
G. Xie
Keyword(s):  
Production Scheduling ◽  
Scheduling Theory ◽  
Optimizing Model

A Design of Model and Algorithm of Intelligent Scheduling System in Enterprise Railway Shunting Plan

2014 ◽  
Vol 496-500 ◽  
pp. 1617-1621
Author(s):  
Bin Ge ◽  
Jiang Hong Han ◽  
Zhen Wei ◽  
Lei Cheng
Keyword(s):  
Production Scheduling ◽  
Algorithm Design ◽  
System Model ◽  
Vehicle Group ◽  
Railway Transport ◽  
New Thought ◽  
Scheduling System ◽  
New Strategy ◽  
Optimizing Model ◽  
Route Search

An intelligent preparation system model of enterprise railway shunting plan was described, and a station-based data structure was established. Through combining vehicle group and discussing route search method, a new thought of algorithm design and project of system implementation was given. A new strategy was proposed for optimizing model and algorithm of enterprise railway transport production scheduling.

Production Scheduling Theory: Just Where Is It Applicable?

2000 ◽  
Vol 30 (6) ◽  
pp. 64-76 ◽  
Author(s):  
Victor Portougal ◽  
David J. Robb
Keyword(s):  
Production Scheduling ◽  
Scheduling Theory

Intelligent Real-Time Control in Manufacturing and Supply Chain Processes

2014 ◽  
Vol 1039 ◽  
pp. 677-685
Author(s):  
Jan Ola Strandhagen ◽  
Emrah Arica ◽  
Heidi C. Dreyer
Keyword(s):  
Decision Support ◽  
Production Scheduling ◽  
Theory And Practice ◽  
Practical Case ◽  
Scheduling Theory ◽  
Real Time Control ◽  
Design And Implementation ◽  
Time Control ◽  
Control Under Uncertainty ◽  
And Control

Production scheduling and control under uncertainty is among the most persistent challenges in the field of operation management. Despite the significant amount of research in this domain, many studies still underline the gap between scheduling theory and practice. In this paper, we outline the important aspects to consider in the design and implementation of decision support systems for the scheduling task by reviewing the literature. From the identified guidelines, we examine a practical case and propose a decision support system for the production scheduling task in an actual manufacturing environment.

Re-Entrant Production Scheduling Problem under Uncertainty Based on QPSO Algorithm

2011 ◽  
Vol 66-68 ◽  
pp. 1061-1066
Author(s):  
Feng Shan Pan ◽  
Chun Ming Ye ◽  
Ji Hua Zhou
Keyword(s):  
Production Scheduling ◽  
Product Life Cycle ◽  
Market Competition ◽  
Product Diversification ◽  
Theoretical Research ◽  
Scheduling Problem ◽  
Scheduling Theory ◽  
Scheduling Problems ◽  
The One ◽  
Construction Strategies

Production scheduling problem is the one of the most basic, important and difficult theoretical research in a manufacturing system. In the past decades of research, the classical scheduling theory has made signficant progress, but the actual scheduling problems are much more complicated than the classical theory. In order to study, the actual scheduling problems are often made much simpler. Therefore, it is difficult for the results of the classical scheduling theory to been put into practice. The considerable gap also exists between the classical scheduling theory and the actual scheduling problem. But with the increasingly fierce market competition, customers have become increasingly demanding product diversification, product life cycle is shorter and more sophisticated structure of the product makes the actual scheduling a large number of uncertainties, the traditional model has become difficult to obtain satisfactory results. This paper makes a analysis on the uncertainties of production scheduling,and tries to solve re-entrant production scheduling problem based on QPSO. It introduces the mathematical model and the solving process based on QPSO algorithm. Then it makes construction strategies to solve it. The paper simulates with Visual C. The results show that this algorithm is feasibility.

Designing a Practical Production Scheduling and Control System: A Case Study in a Norwegian Manufacturing Company

2014 ◽  
Vol 1039 ◽  
pp. 669-676
Author(s):  
Emrah Arica ◽  
Mads Baardsgaard ◽  
Jan Ola Strandhagen
Keyword(s):  
Decision Support ◽  
Production Scheduling ◽  
Theory And Practice ◽  
Practical Case ◽  
Scheduling Theory ◽  
Design And Implementation ◽  
System A ◽  
Control Under Uncertainty ◽  
And Control

Production scheduling and control under uncertainty is among the most persistent challenges in the field of operation management. Despite the significant amount of research in this domain, many studies still underline the gap between scheduling theory and practice. In this paper, we outline the important aspects to consider in the design and implementation of decision support systems for the scheduling task by reviewing the literature. From the identified guidelines, we examine a practical case and propose a decision support system for the production scheduling task in an actual manufacturing environment.

Research on the Production Scheduling Method of a Semiconductor Packaging Test Based With the Clustering Method

2019 ◽  
Vol 12 (2) ◽  
pp. 36-56
Author(s):  
Zhonghua Han ◽  
Quan Zhang ◽  
Yongqing Jiang ◽  
Bin Duan
Keyword(s):  
Production Scheduling ◽  
Clustering Algorithm ◽  
Test Scheduling ◽  
Scheduling Theory ◽  
Simulation Experiments ◽  
The Neural Network ◽  
Network Method ◽  
Scheduling Method ◽  
Semiconductor Packaging ◽  
Ap Clustering

In this article, the scheduling of modern industrial production is studied. The research on scheduling of semiconductor packaging and testing is put forward. A new solution of packaging and test scheduling based on dynamic optimization is proposed. The decomposition strategy is used to solve the problem of the encapsulation test scheduling problem. The complexity of the problem is reduced to ensure the consistency of optimization. In the method, an AP clustering algorithm is used to optimize the matching relationship between job and resource. The neural network method is used to solve the problem. The research of this project will fully combine the characteristics of packaging and testing production. In view of the existing production scheduling theory, there is a big gap to a semiconductor packaging and testing enterprises for the actual research background. This simulation experiments show that the method can be used on packaged production scheduling to provide a viable, effective method support.

Exploring a Mulitcriteria Approach to Production Scheduling

1996 ◽  
Vol 47 (1) ◽  
pp. 162-174
Author(s):  
Valerie Belton ◽  
Mark D Elder
Keyword(s):  
Production Scheduling

Penjadwalan Produksi Menggunakan Metode Simulated Annealing pada Unit Produksi Daun Pintu di PT. ML

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Rosnani Ginting ◽  
Chairul Rahmadsyah Manik
Keyword(s):  
Simulated Annealing ◽  
Problem Solving ◽  
Production Scheduling ◽  
Production Control ◽  
Delivery Time ◽  
Production Schedule ◽  
A Company ◽  
Predetermined Time ◽  
Factory Floor

Penjadwalan merupakan aspek yang sangat penting karena didalamnya terdapat elemen perencanaan dan pengendalian produksi bagi suatu perusahaan yang dapat mengirim barang sesuai dengan waktu yang telah ditentukan, untuk memperoleh waktu total penyelesaian yang minimum. Masalah utama yang dihadapi oleh PT. ML adalah keterlambatan penyelesaian order yang mempengaruhi delivery time ke tangan costumer karena pelaksanaan penjadwalan produksi dilantai pabrik belum menghasilkan makespan yang sesuai dengan order yang ada. Oleh kaena itu dituntut untuk mencari solusi pemecahan masalah optimal dalam penentuan jadwal produksi untuk meminimisasi total waktu penyelessaian (makespan) semua order. Dalam penelitian ini, penjadwalan menggunakan metode Simulated Annealing (SA) diharapkan dapat menghasilkan waktu total penyelesaian lebih cepat dari penjadwalan yang ada pada perusahaan.   Scheduling is a very important aspect because in it there are elements of planning and production control for a company that can send goods in accordance with a predetermined time, to obtain a minimum total time of completion. The main problem faced by PT. ML is the delay in completing orders that affect delivery time to customer because the implementation of production scheduling on the factory floor has not produced the makespan that matches the existing order. Therefore, it is required to find optimal problem solving solutions in determining the production schedule to minimize the total time of elimination (makespan) of all orders. In this study, scheduling using the Simulated Annealing (SA) method is expected to produce a total time of completion faster than the existing scheduling in the company.

Refinery production scheduling toward Industry 4.0

2018 ◽  
Vol 0 (0) ◽  
pp. 0 ◽  
Author(s):  
Marcel JOLY ◽  
Darci ODLOAK ◽  
MarioY. MIYAKE ◽  
Brenno C. MENEZES ◽  
Jeffrey D. KELLY
Keyword(s):  
Production Scheduling ◽  
Industry 4.0 ◽  
Refinery Production
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