job shop
美 
英
- un.现场加工车间；作业安排；零活工场
- 网络机群式布置车间；专门车间；作业车间
英汉解释
例句
As one of the most difficult combinatorial optimization problems, Job-shop Scheduling Problem has always been a hot issue.
作业车间调度问题作为最难的优化组合问题之一，一直以来都是生产调度领域的研究热点。
Hierarchical dispatching rule is a method which optimizes result of job shop scheduling. But building the mode is complicated.
递阶组合规则是一种优化车间作业调度结果的方法，但其构成方式较为复杂。
This model can be used to provide information and decision supporting for the maintenance plan programming and job shop scheduling.
模型可为维修计划的制定和现场的作业调度提供决策支持和信息支持。
This paper presents a complete multiagent framework for dynamic job shop scheduling, with an emphasis on robustness and adaptability.
本文描述了一个完整的为动态车间进度工作表设计的多主体框架，着重强调了此框架的及健全性和适应性。
Job oriented scheduling(JOS) has been the most commonly used in actual job shop scheduling. It loads jobs one by one onto machines.
面向作业调度在当今实际生产企业作业车间调度中得到普遍的应用，其基本思想是将作业一个个地安排到工作机器上。
Job Shop Scheduling is a difficult combinatorial optimization problem and an improved genetic algorithm is used to solve it.
作业车间调度是一类求解困难的组合优化问题，使用改进的遗传算法来求解。
In modern manufacturing enterprises, job-shop scheduling becomes the key to improve enterprises operation efficiency.
在现代制造企业中，车间调度已成为提高企业运行效益的关键环节之一。
Scheduling is a very important job, it has proposed a kind of algorithm for small-batch job shop through detailed description.
作业计划的制定是一项非常重要的工作，通过对作业计划问题的详尽描述，提出了一种用于小批量生产的调度算法。
Then construct a distributed job shop scheduling system around the shop scheduling algorithm, so that it can be applied in practice.
接着围绕车间调度算法构建了分布式的车间调度系统，使其能在实际中得到应用。
Finally, the results from simulation shows the MAS-GA based scheduling system is promising for practical job-shop scheduling.
最后，大量的仿真实验证明了基于MAS和GA的车间调度系统在实际应用中的前景。
A dynamic and real-time system integrating reinforcement learning with simulation is designed for job-shop scheduling.
设计了一个强化学习和仿真相结合的动态实时车间作业排序系统。
In the introduction, it states the significance, recent actuality and research methods of job shop scheduling problem.
全文共分七个章节，首先在第一章绪论中论述了车间调度问题的重要性及其研究现状、方法。
Firstly, a Flexible Job-shop Scheduling model under uncertain information environment is proposed in this thesis.
本文首先建立了不确定信息条件下的柔性作业车间调度模型。
Resource selection in job-shop scheduling has a direct influence on the product quality, date of delivery and production cost.
车间作业计划中的资源选择直接影响到产品的质量、交货期和生产成本。
The whole frame of the scheduling system for the job shop scheduling of transformer with roll-core network manufacturing system is provided.
针对卷铁芯变压器网络化制造车间的调度问题，给出了调度系统的整体框架，将这个网络化制造系统分为两层调度体系。
CIM differs from the traditional job shop manufacturing system in the role the computer plays in the manufacturing process.
CIM与传统的加工车间的制造系统的区别在于计算机在制造过程中所起的作用。
Analyzing the model of the flexible job-shop scheduling problem(FJSP), an immune genetic algorithm(IGA) is proposed to solve the problem.
通过对柔性作业车间调度问题（FJSP）进行分析，借鉴生物免疫机理提出一种求解柔性作业车间调度问题的免疫遗传算法（IGA）。
Four years' experience either in a production or job shop environment.
生产或车间作业四年工作经验。
To overcome prematurity &of genetic algorithm, a new algorithm to solve job-shop scheduling was presented.
为了克服遗传算法早熟和最优解较差的缺点，提出了求解作业车间调度问题的新方法。
The Job Shop Problem (JSP) is a key technology in manufacturing system, and the Q learning was used to realize it.
在制造业系统中车间调度是一项关键技术，可以用强化学习中的Q学习实现对车间作业的动态调度。
The purpose of this paper is using the algorithm to solve the dynamic Job shop scheduling problems.
在此基础上，本文尝试将缩短空闲时间法应用到多作业动态车间作业调度问题上。
Because there is much difficulty in processing in these two types of job shop scheduling, few optional algorithms are available.
由于这两类车间调度问题存在高度的计算难处理性，因而可供选择的算法比较少。
Several stochastic variables are introduced to transform the job-shop scheduling problem into sequential decision problem.
首先引入多个随机变量，将车间作业排序问题转换成序贯决策问题；
The second problem is the fuzzy flexible job shop scheduling problem with preventive maintenance.
第二类问题为具有预防性维修的模糊柔性作业车间调度问题。
A combination decision model of scheduling rules based on simulation is presented for multi-objective problems of job shop scheduling.
针对车间调度规则组合的多目标优化问题，提出了一种基于仿真的评估决策模型。
So, the paper researches on the mold enterprise's job shop scheduling problem.
为此，本文围绕面向模具企业的车间作业调度问题展开研究。
This paper proposes a method of adaptive neural network based on constraint satisfaction for Job Shop Scheduling Problem.
提出一种基于约束满足的自适应神经网络方法求解车间作业调度问题。
The dramatic characteristic of the job shop scheduling problem is its complexity.
车间调度问题的突出特点是其复杂性。
The first problem is the fuzzy flexible job shop scheduling problem.
第一类问题为模糊柔性作业车间调度问题。
and finally proposed an improved ant colony algorithm applying to solve the job shop scheduling problem.
提出了一种改进的蚁群算法应用于解决车间调度问题。
Then, a multi-agent Q-learning algorithm integrated with simulation is developed to solve the job-shop problem.
体Q-学习算法和仿真集成解决作业排序问题；
Then the scheduling model combining monthly plan scheduling and re-scheduling is proposed based on the job-shop scheduling model.
并以调度模型为核心，设计并实现了某船厂的涂装生产管理系统。
Facility layout of job shop problem is non-linear and NP-complete characteristic, and can not he solved well by conventional methods.
车间设备布局问题具有非线性、NP难等特性，无法运用传统方法求得最优解。
It is difficult to get the absolute position of magnets because of obstacle in job-shop and this often causes trouble in debugging AGV.
车间环境障碍使得磁钉的绝对位置难以精确测量，给AGV的实际应用调试带来不便。
The Job shop scheduling problem is a combinatorial optimum problem that is constrained with time, sequence and resource.
车间作业调度问题是一类具有时间约束、次序约束和资源约束的组合优化问题。
Performance Analysis of a Multi-objective Immune Genetic Algorithm and its Applications to Flexible Job Shop Scheduling
多目标免疫遗传算法性能分析及其在柔性作业车间调度中的应用
Application of Particle Swarm Optimization with Adaptive Mutation to Job Shop Scheduling Problem and Its Software Implementation
基于自适应变异的粒子群优化算法的车间作业调度优化及其软件实现
Adaptive Ant Colony Algorithm and Its Application to Multi-restriction Multi-Objective Flexible Job-Shop Scheduling
自适应蚁群算法及其在多约束多目标柔性Job-Shop调度中的应用
Study on the General Hybrid Genetic Algorithm for Job Shop Scheduling
求解作业排序问题的通用混合遗传算法研究
Cooperative optimization algorithms used in job shop scheduling problem
作业车间调度问题中的协同优化算法
