An adaptive approach in production scheduling based on the mixed graph model

1994 ◽  
Author(s):  
Yu.N. Sotskov
Keyword(s):  
Production Scheduling ◽  
Graph Model ◽  
Mixed Graph ◽  
Adaptive Approach

A Hybrid Swarm Optimization Algorithm for Complex Assignment Problem

2010 ◽  
Vol 26-28 ◽  
pp. 1151-1154
Author(s):  
Zong Li Liu ◽  
Jie Cao ◽  
Zhan Ting Yuan
Keyword(s):  
Assignment Problem ◽  
Production Scheduling ◽  
Large Scale ◽  
Optimization Problems ◽  
Graph Model ◽  
Task Assignment ◽  
Hybrid Swarm ◽  
Swarm Optimization ◽  
Computing Technique ◽  
Task Assignment Problem

The optimization of complex systems, such as production scheduling systems and control systems, often encounters some difficulties, such as large-scale, hard to model, time consuming to evaluate, NP-hard, multi-modal, uncertain and multi-objective, etc. It is always a hot research topic in academic and engineering fields to propose advanced theory and effective algorithms. As a novel evolutionary computing technique, particle swarm optimization (PSO) is characterized by not being limited by the representation of the optimization problems, and by global optimization ability, which has gained wide attentation and research from both academic and industry fields. The task assignment problem in the enterprise with directed graph model is presented. Task assignment problem with buffer zone is solved via a hybrid PSO algorithm. Simulation result shows that the model and the algorithm are effective to the problem.

Dense subgraph mining with a mixed graph model

2013 ◽  
Vol 34 (11) ◽  
pp. 1252-1262 ◽  
Author(s):  
Anita Keszler ◽  
Tamás Szirányi ◽  
Zsolt Tuza
Keyword(s):  
Graph Model ◽  
Dense Subgraph ◽  
Mixed Graph ◽  
Subgraph Mining ◽  
Dense Subgraph Mining

Adaptive scheduling algorithm based on mixed graph model

1996 ◽  
Vol 143 (1) ◽  
pp. 9-16 ◽  
Author(s):  
N.V. Shakhlevich ◽  
Y.N. Sotskov ◽  
F. Werner
Keyword(s):  
Scheduling Algorithm ◽  
Graph Model ◽  
Adaptive Scheduling ◽  
Mixed Graph

scholarly journals Scheduling approach for on-site jobs of service providers

2019 ◽  
Vol 32 (4) ◽  
pp. 913-948 ◽  
Author(s):  
Tibor Holczinger ◽  
Olivér Ősz ◽  
Máté Hegyháti
Keyword(s):  
Production Scheduling ◽  
Service Providers ◽  
Cost Minimization ◽  
Graph Model ◽  
Scheduling Problems ◽  
Successful Operation ◽  
Trained Personnel ◽  
The Given ◽  
A Company ◽  
Timing Requirement

AbstractNowadays the successful operation of a company is unimaginable without fast and reliable communication. As a result, so-called Communication Service Providers play an important role in today’s business life. Their orders have to be carried out promptly and dependably, let them be requests for new installations, modifications, or maintenance tasks. These orders have to be performed at different locations and they often have deadlines or strict starting times. Violating such a timing requirement usually implies penalties. In this paper, scheduling problems arising at a Hungarian service provider are examined. At this company, orders are decomposed into smaller tasks, which can be performed by specially trained personnel. Transportation of these specialists contributes a lot to the costs and to the complexity of their scheduling, as well. The goal is to minimize the overall cost of satisfying all orders within the given time horizon with the available assets of the company. The proposed approach relies on the S-graph framework, which has been applied to various production scheduling problems in the literature. In addition to an unambiguous and sound S-graph model of the examined problem, slight modifications of the scheduling algorithms for cost minimization, and new bounding methods have been developed. Several of such bounds have been provided and tested for performance and scalability over a large number of generated examples. The sensitivity of the approach for certain problem features has also been examined.

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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