Optimization of Dynamic Job-Shop Scheduling Based on Game Theory

Nash Equilibrium Point ◽

Shop Scheduling ◽

Scheduling Model ◽

Dynamic Rescheduling ◽

To deal with uncertain dynamic interferences occurred in the workshop, and meet the competition requirements of jobs submitted by different customers, a dynamic job-shop scheduling model based on game theory is presented. In order to find the Nash equilibrium point of the model effectively, dynamic rescheduling judgment based on event-driven policy is adopted, and a hybrid genetic algorithm is designed. The case study is carried out to demonstrate the validity of above dynamic job-shop scheduling methods.

Preliminary Work Towards Development of a Dynamic Job Shop Scheduling Model

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.845.682 ◽

2013 ◽

Vol 845 ◽

pp. 682-686

Author(s):

Wan Nazdah Wan Hussin ◽

Adnan Hassan ◽

A.H. Halim ◽

Z. Zakaria

Keyword(s):

Job Shop ◽

Job Shop Scheduling ◽

Shop Scheduling ◽

Basic Model ◽

Spreadsheet Model ◽

Scheduling Model ◽

Preliminary Work ◽

Dynamic Factors ◽

This paper presents a preliminary work on a development of dynamic job shop scheduling model. The motivation of the study comes from an urgent need for practical procedures to enable easier and accurate feedback at operational level particularly related to job shop in small and medium-sized companies. A spreadsheet-based scheduling template is formulated and modeled using Microsoft Excel. A job shop benchmark case study available in OR-Library has been chosen to demonstrate the applicability of the basic model. The preliminary result indicating that the proposed spreadsheet model needs further refinement through incorporation of dynamic factors to be obtained from industrial practitioners.

Research of Multi-resource Dynamic Job-Shop Scheduling Based on the Hybrid Genetic Algorithm

2009 Third International Conference on Genetic and Evolutionary Computing ◽

10.1109/wgec.2009.31 ◽

2009 ◽

Cited By ~ 1

Author(s):

Zhao Peng ◽

Huang Ting-lei

Keyword(s):

Genetic Algorithm ◽

Job Shop ◽

Job Shop Scheduling ◽

Shop Scheduling ◽

2016 International Conference on Information & Communication Technology and Systems (ICTS) ◽

Job-Shop Scheduling model for optimization of the double track railway scheduling: (Case study: Solo-Yogyakarta railway network)

10.1109/icts.2016.7910279 ◽

2016 ◽

Author(s):

Sarngadi Palgunadi ◽

Dian Supraba ◽

Bambang Harjito

Keyword(s):

Job Shop ◽

Job Shop Scheduling ◽

Railway Network ◽

Shop Scheduling ◽

Scheduling Model ◽

Double Track

A dynamic job-shop scheduling model based on deep learning

Advances in Production Engineering & Management ◽

10.14743/apem2021.1.382 ◽

2021 ◽

Vol 16 (1) ◽

pp. 23-36

Author(s):

W. Tian ◽

H.P. Zhang

Keyword(s):

Deep Learning ◽

Job Shop ◽

Short Term Memory ◽

Job Shop Scheduling ◽

Core Competitiveness ◽

Shop Scheduling ◽

Multi Objective ◽

Model Based ◽

Scheduling Model ◽

Ideally, the solution to job-shop scheduling problem (JSP) should effectively reduce the cost of manpower and materials, thereby enhancing the core competitiveness of the manufacturer. Deep learning (DL) neural networks have certain advantages in handling complex dynamic JSPs with a massive amount of historical data. Therefore, this paper proposes a dynamic job-shop scheduling model based on DL. Firstly, a data prediction model was established for dynamic job-shop scheduling, with long short-term memory network (LSTM) as the basis; the Dropout technology and adaptive moment estimation (ADAM) were introduced to enhance the generalization ability and prediction effect of the model. Next, the dynamic JSP was described in details, and three objective functions, namely, maximum makespan, total device load, and key device load, were chosen for optimization. Finally, the multi-objective problem of dynamic JSP scheduling was solved by the improved multi-objective genetic algorithm (MOGA). The effectiveness of the algorithm was proved experimentally.

Inventory based two-objective job shop scheduling model and its hybrid genetic algorithm

Applied Soft Computing ◽

10.1016/j.asoc.2012.03.073 ◽

2013 ◽

Vol 13 (3) ◽

pp. 1400-1406 ◽

Cited By ~ 20

Author(s):

Ren Qing-dao-er-ji ◽

Yuping Wang ◽

Xiaoli Wang

Keyword(s):

Genetic Algorithm ◽

Job Shop ◽

Job Shop Scheduling ◽

Shop Scheduling ◽

Scheduling Model

Research on Dynamic Job Shop Scheduling Problem Base on Hybrid Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.198-199.1413 ◽

2012 ◽

Vol 198-199 ◽

pp. 1413-1416 ◽

Cited By ~ 1

Author(s):

Cun Liang Yan ◽

Wei Feng Shi ◽

Ze Ming Zou

Keyword(s):

Genetic Algorithm ◽

Job Shop ◽

Dynamic Scheduling ◽

Job Shop Scheduling ◽

Scheduling Problem ◽

Job Shop Scheduling Problem ◽

Shop Scheduling ◽

Stochastic Events ◽

In real production processing, job shop scheduling problem (JSP) is often express as dynamic scheduling problem. In this article a hybrid genetic algorithm and handling strategies are used for real job shop scheduling problem. It gives the scheduling result with the appropriate handling strategies to the stochastic events such as equipment breakdown and urgent orders. The data of Shanghai Shen Mo Die & Mold Manufacturing Co., Ltd (ShenMo) is used for the application of dynamic scheduling simulation, and the results of which show that the proposed method can satisfactorily solve the stochastic events of scheduling.