Flexible integrated scheduling algorithm base on static processing time

2011 ◽  
Author(s):  
Zhiqiang Xie ◽  
Peng Wang ◽  
Ningning Chang ◽  
Xia Shao
Keyword(s):  
Processing Time ◽  
Scheduling Algorithm ◽  
Integrated Scheduling ◽  
Algorithm Base

A multi-shop integrated scheduling algorithm with fixed output constraint

2021 ◽  
pp. 1-9
Author(s):  
Yingchun Xia ◽  
Zhiqiang Xie ◽  
Yu Xin ◽  
Xiaowei Zhang
Keyword(s):  
Constraint Programming ◽  
Programming Model ◽  
Scheduling Algorithm ◽  
Processing Parameters ◽  
Scheduling Problem ◽  
Integrated Scheduling ◽  
Scheduling Scheme ◽  
Wide Range ◽  
Constraint Programming Model ◽  
Output Constraint

The customized products such as electromechanical prototype products are a type of product with research and trial manufacturing characteristics. The BOM structures and processing parameters of the products vary greatly, making it difficult for a single shop to meet such a wide range of processing parameters. For the dynamic and fuzzy manufacturing characteristics of the products, not only the coordinated transport time of multiple shops but also the fact that the product has a designated output shop should be considered. In order to solve such Multi-shop Integrated Scheduling Problem with Fixed Output Constraint (MISP-FOC), a constraint programming model is developed to minimize the total tardiness, and then a Multi-shop Integrated Scheduling Algorithm (MISA) based on EGA (Enhanced Genetic Algorithm) and B&B (Branch and Bound) is proposed. MISA is a hybrid optimization method and consists of four parts. Firstly, to deal with the dynamic and fuzzy manufacturing characteristics, the dynamic production process is transformed into a series of time-continuous static scheduling problem according to the proposed dynamic rescheduling mechanism. Secondly, the pre-scheduling scheme is generated by the EGA at each event moment. Thirdly, the jobs in the pre-scheduling scheme are divided into three parts, namely, dispatched jobs, jobs to be dispatched, and jobs available for rescheduling, and at last, the B&B method is used to optimize the jobs available for rescheduling by utilizing the period when the dispatched jobs are in execution. Google OR-Tools is used to verify the proposed constraint programming model, and the experiment results show that the proposed algorithm is effective and feasible.

scholarly journals An Efficient Framework to Improve QoS of CSP using Enhanced Minimal Resource Optimization based Scheduling Algorithm

2018 ◽  
Vol 12 (3) ◽  
pp. 1179
Author(s):  
Ravi Mahadevan ◽  
Neelamegam Anbazhagan
Keyword(s):  
Processing Time ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Daily Basis ◽  
Resource Optimization ◽  
Cloud Environment ◽  
Bandwidth Utilization ◽  
Scheduling Policy ◽  
Minimal Resource

<span>Online Nowadays, the enterprises &amp; individuals are contributing their workloads on cloud service providers which are going to increase on daily basis. There are   large amount CSP are available to offer virtualized and dynamic resource on pay and use basis. However, there are almost CSP failed to maintain quality of service (QOS) and minimal resource optimization. Some of the existing approaches are highly dedicated on scheduling policy but, it does not considered reliable services with optimized QOS. To offer best solution of above problem, the framework proposes Enhanced Minimal Resource Optimization based Scheduling Algorithm to minimize the resources and maintain the QOS.  The method avoids delay in Request-Response model in cloud environment. To avoid overload for resource allocation, the proposed design utilized optimized scheduling policy.  Proposed mechanisms utilized optimized service brokering policy to reduce the delay response in cloud environment. The framework also help cloud user to prefer best CSP according to their prior services. The method offers rising trend of resource based structure to reduce the placement churn extensively. Proposed system utilized efficient scheduling policy to transmit data request to CSP with minimal data processing time. The entire utilization is to improve the QOS of cloud service provider in the features of multi-dimensional resource. Based on experimental evaluations, proposed technique improves the CPT (Computation Processing Time) 301.72 milliseconds, BU (Bandwidth Utilization) 20 Mbps, CPUU (CPU Utilization) 5% &amp; MRU (Memory Resource Utilization) 3% on given input parameters compare than existing methodology.</span>

An Effective Memetic Algorithm for the Distributed Integrated Scheduling of Tree-Structured Products

2021 ◽  
pp. 2150001
Author(s):  
Yilong Gao ◽  
Zhiqiang Xie ◽  
Qing Jia ◽  
Xu Yu
Keyword(s):  
Sampling Method ◽  
Memetic Algorithm ◽  
Scheduling Algorithm ◽  
Optimal Solution ◽  
Estimation Algorithm ◽  
Probability Models ◽  
Complex Products ◽  
Integrated Scheduling ◽  
Local Search Strategy ◽  
Representation Method

Aiming at the distributed integrated scheduling of complex products with tree structure, a memetic algorithm-based distributed integrated scheduling algorithm is proposed. Based on the framework of the memetic algorithm, the algorithm uses a distributed estimation algorithm for global search and performs a local search strategy based on the critical operation set for the current optimal solution obtained in each evolutionary generation. A bi-chain-based individual representation method is presented and a simple greedy insertion-based decoding method is given; two position-based probability models are built, which are used to describe the distribution of the operation priority and factory assignment, respectively. Based on the designed probability models, two learning-based updating mechanisms and an improved sampling method are given, which ensures that the population evolves towards a promising region. In order to enhance the searchability for the superior solutions, nine disturbance operators based on the critical operation set are presented. The parameters are determined by the design-of-experiment (DOE) test, and the effectiveness of the proposed algorithm is verified by comparative experiments.

Energy-efficient multi-objective scheduling algorithm for hybrid flow shop with fuzzy processing time

2019 ◽  
Vol 233 (10) ◽  
pp. 1282-1297 ◽  
Author(s):  
Binghai Zhou ◽  
Wenlong Liu
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Processing Time ◽  
Flow Shop ◽  
Scheduling Algorithm ◽  
Mixed Integer ◽  
Computational Time ◽  
Hybrid Flow Shop ◽  
Multi Objective ◽  
Fuzzy Processing Time

Increasing costs of energy and environmental pollution is prompting scholars to pay close attention to energy-efficient scheduling. This study constructs a multi-objective model for the hybrid flow shop scheduling problem with fuzzy processing time to minimize total weighted delivery penalty and total energy consumption simultaneously. Setup times are considered as sequence-dependent, and in-stage parallel machines are unrelated in this model, meticulously reflecting the actual energy consumption of the system. First, an energy-efficient bi-objective differential evolution algorithm is developed to solve this mixed integer programming model effectively. Then, we utilize an Nawaz-Enscore-Ham-based hybrid method to generate high-quality initial solutions. Neighborhoods are thoroughly exploited with a leader solution challenge mechanism, and global exploration is highly improved with opposition-based learning and a chaotic search strategy. Finally, problems in various scales evaluate the performance of this green scheduling algorithm. Computational experiments illustrate the effectiveness of the algorithm for the proposed model within acceptable computational time.

F-0619 Job Shop Scheduling Algorithm Base on Tabu Search

2001 ◽  
Vol III.01.1 (0) ◽  
pp. 339-340
Author(s):  
Jiahua WENG ◽  
Hiroki OKUBO ◽  
Hisashi ONARI
Keyword(s):  
Tabu Search ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Algorithm ◽  
Shop Scheduling ◽  
Algorithm Base

scholarly journals Integrated Scheduling Algorithm of Complex Product with No-wait Constraint Based on Virtual Component

2020 ◽  
Vol 56 (4) ◽  
pp. 246
Author(s):  
GUO Weifei ◽  
LEI Qi ◽  
SONG Yuchuan ◽  
Lü Xiangfei ◽  
LI Lei
Keyword(s):  
Scheduling Algorithm ◽  
Complex Product ◽  
Integrated Scheduling ◽  
No Wait

scholarly journals Integrated scheduling algorithm for multiple complex products with due date constraints

2021 ◽  
Vol 1748 ◽  
pp. 032030
Author(s):  
Xinkun Wang ◽  
Yuchuan Song ◽  
Yuji Zou ◽  
Weifei Guo ◽  
Yi Wang
Keyword(s):  
Scheduling Algorithm ◽  
Due Date ◽  
Complex Products ◽  
Integrated Scheduling
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