Linear Rail Space Dynamic Scheduling Technology for Multi-Tasking Hybrid Assembly Sections

2012 ◽  
Vol 271-272 ◽  
pp. 650-656
Author(s):  
Zhi Bing Lu ◽  
Ai Min Wang ◽  
Cheng Tong Tang ◽  
Jing Sheng Li
Keyword(s):  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Real Data ◽  
Utilization Rate ◽  
Filter Method ◽  
Scheduling Problem ◽  
Rule Based ◽  
Comprehensive Utilization ◽  
Space Production

For the rapid response to production scheduling problem driven by high-density production tasks, a dynamic scheduling technology for the large precision strip products assembly with a mixture of task time nodes and line-rail space is proposed. A scheduling constrained model containing coverage, proximity, timeliness and resource is established. A linear rail space production scheduling technology using heuristic automatic scheduling and event-driven method is put forward. The time rule based on delivery and single completion assembly is formed, at the same time the space rule based on the adjacent rail and comprehensive utilization is researched. Supposing the privilege of single product assembling as the core, the scheduling parts filter method based on multiple constraints and former rules. For the space layout problem, a clingy forward and backward algorithms is proposed to judge the assemble position regarding the space comprehensive utilization rate. The classification of the various disturbances in the actual production is summarized. Three basic algorithms are proposed, including insertion, moving and re-scheduling algorithm, in order to solve the assembly dynamic scheduling problem driven by production disturbance events. Finally, take rocket as the example， the rocket assembly space production scheduling system is developed, combining with the proposed algorithm. The practicability of the system is validated using real data.

Research on GA-DPSO Virtual Machine Scheduling Algorithm Based on Comprehensive Utilization of Host Resource

2013 ◽  
Vol 791-793 ◽  
pp. 1373-1376
Author(s):  
Shu Huang ◽  
Jing Bo Yang ◽  
Hui Jie Ding
Keyword(s):  
Virtual Machine ◽  
Particle Swarm Optimization Algorithm ◽  
Scheduling Algorithm ◽  
Utilization Rate ◽  
Business Systems ◽  
Management Level ◽  
Comprehensive Utilization ◽  
Virtualization Technology ◽  
Optimum Balance ◽  
Host Resource

Virtualization technology has been widely used. Modern data center uses different equipments to support a large number of business systems. Whether the resources scheduling of virtual machine can be realized has become a very important issue, which will reflect the data centers management level of intelligence, intensiveness and automation. On the basis of comprehensive utilization of the physical machines various resources, the algorithm combines the advantages of genetic algorithm with particle swarm optimization algorithm, with reference to model of load balancing scheduling system, constantly adjusts to the load on the host, and consequently achieves the optimum balance of comprehensive utilization rate of different host resources.

scholarly journals Research on Optimization of Production Decision Based on Payment Time and Price Coordination

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yanyang Yan ◽  
Liang Yuan ◽  
Yemei Li
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Production Scheduling ◽  
Management Practice ◽  
Scheduling Algorithm ◽  
Scheduling Problem ◽  
Effective Implementation ◽  
The Mathematical Model ◽  
Production Decision

This paper focuses on the coordination and optimization between a manufacturer and multiple retailers in a supply chain. The manufacturer makes product quotes and delivery deadlines for all retailers, and each retailer selects product offers and delivery deadlines based on their own needs. Manufacturers maximize their own total profits by setting optimal quotes and delivery deadlines. This paper constructs the mathematical model of the optimal quotation and delivery deadline and proposes a scheduling algorithm that is different from the general M/M/1 and then studies the production scheduling problem and explores the effective implementation of quotation policy in management practice.

scholarly journals Sustainable Production Scheduling in Open Innovation Perspective under the Fourth Industrial Revolution

2018 ◽  
Vol 4 (4) ◽  
pp. 42 ◽  
Author(s):  
Sang-Oh Shim ◽  
KyungBae Park ◽  
SungYong Choi
Keyword(s):  
Production Scheduling ◽  
Open Innovation ◽  
Industrial Revolution ◽  
Scheduling Algorithm ◽  
Point Of View ◽  
Scheduling Problem ◽  
Planning And Scheduling ◽  
Real Time Scheduling ◽  
Fourth Industrial Revolution ◽  
Operation Scheduling

This research addresses a specific issue in the field of operation scheduling. Even though there are lots of researches on the field of planning and scheduling, a specific scheduling problem is introduced here. We focus on the operation scheduling requirements that the Fourth Industrial Revolution has brought currently. From the point of view of open innovation, operation scheduling is known as the one that is using the Internet of Things, Cloud Computing, Big Data, and Mobile technology. To build proper operation systems under the Fourth Industrial Revolution, it is very essential to devise effective and efficient scheduling methodology to improve product quality, customer delivery, manufacturing flexibility, cost saving, and market competence. A scheduling problem on designated parallel equipments, where some equipments are grouped according to the recipe of lots, is considered. This implies that a lot associated with a specific recipe is preferred to be processed on an equipment among predetermined (designated) ones regardless of parallel ones. A setup operation occurs between different recipes of lots. In order to minimize completion time of the last lot, a scheduling algorithm is proposed. We conducted a simulation study with randomly generated problems, and the proposed algorithm has shown desirable and better performance that can be applied in real-time scheduling.

scholarly journals Clock Compensation Strategy in Train Ethernet

2013 ◽  
Vol 347-350 ◽  
pp. 2061-2066
Author(s):  
Xiao Yong Zhang ◽  
Jun Peng ◽  
Shuo Li
Keyword(s):  
Reinforcement Learning ◽  
Communication Networks ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Problem ◽  
Gateway Node ◽  
Adaptive Weights ◽  
Network Load ◽  
Queue Scheduling ◽  
The Stability

How to degrade the delay time of gateway queuing with heavy network load in train communication networks is the key to guarantee the stability of the train. This article models the queue scheduling problem modeling into reinforcement learning process, puts forward an adaptive weights learning polling scheduling algorithm with the purpose of dynamic scheduling for vehicle gateway node queue. With the compare of algorithm in this paper and weighted round-robin scheduling algorithm in adequate and inadequate bandwidth resources situations, we have approved the superiority of the algorithm in this paper.

A Review on Dynamic Production Scheduling and Solvable Algorithms

2012 ◽  
Vol 622-623 ◽  
pp. 1815-1820
Author(s):  
Guo Jin Hu ◽  
Pin Xin Fu ◽  
Mei Lin Wang ◽  
Qing Yun Dai ◽  
Jian Cong Song
Keyword(s):  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Real Life ◽  
Research Direction ◽  
Future Research ◽  
Machine Breakdown ◽  
Advantages And Disadvantages ◽  
Engineering Changes ◽  
Dynamic Production

Dynamic production scheduling (DPS) is usually trigged by uncertain disturbances such as emergency orders, machine breakdown and rolling planning horizon etc. DPS is a challenging problem in real-life industry manufacturing field due to its bulky problem scalability, which is more significant in discrete manufacturing industry. This industry features multi-specifications, small batch and customization production pattern in terms of its production characteristics and workshop scheduling algorithm whose multi-product series are subject to complexity, multi- various constrains, multi-dynamic objectives and uncertainties. In order to card this research direction, this paper reviews it given different disturbances including emergency orders, machine breakdown, tardiness of job, and engineering changes. Moreover, currently common advantages and disadvantages of dynamic scheduling algorithm are laid stress on. Accordingly, characteristics and future research direction of it are presented. For different disturbances, corresponding algorithm solutions are categorized and reviewed. It aims at guiding the academics and practitioners to choose the efficient and effective solutions when facing different situations.

A Novel Scheduling Algorithm Based on Game Theory and Reinforcement Learning

2011 ◽  
Vol 66-68 ◽  
pp. 1948-1953
Author(s):  
Wen Sheng Zou
Keyword(s):  
Game Theory ◽  
Reinforcement Learning ◽  
Bin Packing ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Learning Approach ◽  
Scheduling Problem ◽  
Power Scheduling ◽  
Long Duration ◽  
Better Than

In this paper we proposed a new dynamic scheduling algorithm for power scheduling problem. The algorithm is based on game theory and reinforcement learning approach. We compared the performance of our algorithm with that of online bin packing and MAB algorithm. We observed that our algorithm performs better than online bin packing when there is a variation in the deadlines. This is because our algorithm schedules the requests on the basis of their actions and the probability of missing the deadline and online bin packing algorithm schedules requests based on the sequence of requests as they arrive. We observed that our approach is more useful, when scheduling requests repeat themselves for long duration.

scholarly journals A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

2020 ◽  
Vol 10 (2) ◽  
pp. 460
Author(s):  
Bin Zhang ◽  
Dawei Wu ◽  
Yingjie Song ◽  
Kewei Liu ◽  
Juxia Xiong
Keyword(s):  
Approximation Algorithm ◽  
Production Scheduling ◽  
Manufacturing Systems ◽  
Scheduling Algorithm ◽  
Fast Algorithms ◽  
Batch Scheduling ◽  
Scheduling Problem ◽  
Total Size ◽  
Processing Times ◽  
Batch Processing Machine

With the rapid economic development, manufacturing enterprises are increasingly using an efficient workshop production scheduling system in an attempt to enhance their competitive position. The classical workshop production scheduling problem is far from the actual production situation, so it is difficult to apply it to production practice. In recent years, the research on machine scheduling has become a hot topic in the fields of manufacturing systems. This paper considers the batch processing machine (BPM) scheduling problem for scheduling independent jobs with arbitrary sizes. A novel fast parallel batch scheduling algorithm is put forward to minimize the makespan in this paper. Each of the machines with different capacities can only handle jobs with sizes less than the capacity of the machine. Multiple jobs can be processed as a batch simultaneously on one machine only if their total size does not exceed the machine capacity. The processing time of a batch is determined by the longest of all the jobs processed in the batch. A novel and fast 4.5-approximation algorithm is developed for the above scheduling problem. For the special case of all the jobs having the same processing times, a simple and fast 2-approximation algorithm is achieved. The experimental results show that fast algorithms further improve the competitive ratio. Compared to the optimal solutions generated by CPLEX, fast algorithms are capable of generating a feasible solution within a very short time. Fast algorithms have less computational costs.

Dual priority dynamic scheduling algorithm based on multi-FPGA

2013 ◽  
Vol 33 (3) ◽  
pp. 862-865
Author(s):  
Shuangzhi DU ◽  
Yong WANG ◽  
Xiaoling TAO
Keyword(s):  
Dynamic Scheduling ◽  
Scheduling Algorithm
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