scholarly journals A Hyper Heuristic Algorithm Based Genetic Programming for Steel Production Scheduling of Cyber-Physical System-ORIENTED

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2256
Author(s):  
Xiaowu Chen ◽  
Guozhang Jiang ◽  
Yongmao Xiao ◽  
Gongfa Li ◽  
Feng Xiang
Keyword(s):  
Genetic Programming ◽  
Heuristic Algorithm ◽  
Production Scheduling ◽  
Physical System ◽  
Dynamic Scheduling ◽  
Steel Production ◽  
Intelligent Manufacturing ◽  
Selection Strategy ◽  
Cyber Physical System ◽  
Scheduling Problems

Intelligent manufacturing is the trend of the steel industry. A cyber-physical system oriented steel production scheduling system framework is proposed. To make up for the difficulty of dynamic scheduling of steel production in a complex environment and provide an idea for developing steel production to intelligent manufacturing. The dynamic steel production scheduling model characteristics are studied, and an ontology-based steel cyber-physical system production scheduling knowledge model and its ontology attribute knowledge representation method are proposed. For the dynamic scheduling, the heuristic scheduling rules were established. With the method, a hyper-heuristic algorithm based on genetic programming is presented. The learning-based high-level selection strategy method was adopted to manage the low-level heuristic. An automatic scheduling rule generation framework based on genetic programming is designed to manage and generate excellent heuristic rules and solve scheduling problems based on different production disturbances. Finally, the performance of the algorithm is verified by a simulation case.

Steelmaking-Hot Rolling Scheduling Model and Method for Integrated Management in Iron and Steel Enterprises

2013 ◽  
Vol 860-863 ◽  
pp. 3094-3099 ◽  
Author(s):  
Bao Lin Zhu ◽  
Shou Feng Ji
Keyword(s):  
Production Scheduling ◽  
Integrated Management ◽  
Steel Production ◽  
Optimal Solution ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Iron And Steel ◽  
Scheduling Model ◽  
General Production ◽  
Iron And Steel Production

Iron and steel production scheduling problems are different from general production scheduling in machine industry. They have to meet special demands of steel production process. The CCR production manner dramatically promotes the revolution in technology and management, especially to planning and scheduling. In this paper, a scheduling model is presented to integrate the three working procedures and the lagrangian relaxation technology is proposed to get the optimal solution of the scheduling model. Finally, numerical examples are given to demonstrate the effectiveness of the integrated model and method.

A FMS Dynamic Scheduling Optimization Strategy and Simulation Research

2013 ◽  
Vol 389 ◽  
pp. 692-697
Author(s):  
Ji Zhuang Hui ◽  
Xiang Ding ◽  
Kai Gao
Keyword(s):  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Scheduling Problems ◽  
Optimization Strategy ◽  
Scheduling Optimization ◽  
Simulation Research ◽  
Scheduling Strategy ◽  
Machine Failure ◽  
Rolling Window ◽  
Scheduling Optimization Algorithm

This paper studied the FMS dynamic scheduling problem which was based on Petri net FMS static scheduling optimization algorithm, which in accorder to solve the FMS actual production scheduling problems. A rolling window dynamic re-scheduling strategy was proposed which based on event driven and cycle driven. Then take the emergency machine failure often appearing in the actual workshop for example, this scheduling strategy was analyzed and applied to dynamic simulation and finally the effectiveness of the dynamic scheduling strategy was verified.

scholarly journals A Combination of Palmer Algorithm and Gupta Algorithm for Scheduling Problem in Apparel Industry

2021 ◽  
Vol 11 (1) ◽  
pp. 1-12
Author(s):  
Cecilia E. Nugraheni ◽  
Luciana Abednego ◽  
Maria Widyarini
Keyword(s):  
Genetic Programming ◽  
Computer Program ◽  
Production Scheduling ◽  
Textile Industry ◽  
Flow Shop ◽  
Apparel Industry ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Shop Scheduling

The apparel industry is a class of textile industry. Generally, the production scheduling problem in the apparel industry belongs to Flow Shop Scheduling Problems (FSSP). There are many algorithms/techniques/heuristics for solving FSSP. Two of them are the Palmer Algorithm and the Gupta Algorithm. Hyper-heuristic is a class of heuristics that enables to combine of some heuristics to produce a new heuristic. GPHH is a hyper-heuristic that is based on genetic programming that is proposed to solve FSSP [1]. This paper presents the development of a computer program that implements the GPHH. Some experiments have been conducted for measuring the performance of GPHH. From the experimental results, GPHH has shown a better performance than the Palmer Algorithm and Gupta Algorithm.

Implementation of a Cyber-Physical System Using Wireless Sensor Networks for Monitoring Patients

2015 ◽  
Vol 1 ◽  
pp. 26 ◽  
Author(s):  
Vo Que Son ◽  
Do Tan A
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Physical System ◽  
Patient Monitoring ◽  
High Reliability ◽  
Vital Signs ◽  
Wireless Sensor ◽  
Cyber Physical System ◽  
Self Administration ◽  
Hospital Units

Sensing, distributed computation and wireless communication are the essential building components of a Cyber-Physical System (CPS). Having many advantages such as mobility, low power, multi-hop routing, low latency, self-administration, utonomous data acquisition, and fault tolerance, Wireless Sensor Networks (WSNs) have gone beyond the scope of monitoring the environment and can be a way to support CPS. This paper presents the design, deployment, and empirical study of an eHealth system, which can remotely monitor vital signs from patients such as body temperature, blood pressure, SPO2, and heart rate. The primary contribution of this paper is the measurements of the proposed eHealth device that assesses the feasibility of WSNs for patient monitoring in hospitals in two aspects of communication and clinical sensing. Moreover, both simulation and experiment are used to investigate the performance of the design in many aspects such as networking reliability, sensing reliability, or end-to-end delay. The results show that the network achieved high reliability - nearly 97% while the sensing reliability of the vital signs can be obtained at approximately 98%. This indicates the feasibility and promise of using WSNs for continuous patient monitoring and clinical worsening detection in general hospital units.

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