job shop
美 
英
- un.現場加工車間；作業安排；零活工場
- 網絡機群式布置車間；專門車間；作業車間
英漢解釋
例句
As one of the most difficult combinatorial optimization problems, Job-shop Scheduling Problem has always been a hot issue.
作業車間調度問題作為最難的優化組合問題之一，一直以來都是生產調度領域的研究熱點。
Hierarchical dispatching rule is a method which optimizes result of job shop scheduling. But building the mode is complicated.
遞階組合規則是一種優化車間作業調度結果的方法，但其構成方式較為復雜。
This model can be used to provide information and decision supporting for the maintenance plan programming and job shop scheduling.
模型可為維修計劃的制定和現場的作業調度提供決策支持和信息支持。
This paper presents a complete multiagent framework for dynamic job shop scheduling, with an emphasis on robustness and adaptability.
本文描述了一個完整的為動態車間進度工作表設計的多主體框架，著重強調了此框架的及健全性和適應性。
Job oriented scheduling(JOS) has been the most commonly used in actual job shop scheduling. It loads jobs one by one onto machines.
面向作業調度在當今實際生產企業作業車間調度中得到普遍的應用，其基本思想是將作業一個個地安排到工作機器上。
Job Shop Scheduling is a difficult combinatorial optimization problem and an improved genetic algorithm is used to solve it.
作業車間調度是一類求解困難的組合優化問題，使用改進的遺傳算法來求解。
In modern manufacturing enterprises, job-shop scheduling becomes the key to improve enterprises operation efficiency.
在現代制造企業中，車間調度已成為提高企業運行效益的關鍵環節之一。
Scheduling is a very important job, it has proposed a kind of algorithm for small-batch job shop through detailed description.
作業計劃的制定是一項非常重要的工作，通過對作業計劃問題的詳盡描述，提出了一種用于小批量生產的調度算法。
Then construct a distributed job shop scheduling system around the shop scheduling algorithm, so that it can be applied in practice.
接著圍繞車間調度算法構建了分布式的車間調度系統，使其能在實際中得到應用。
Finally, the results from simulation shows the MAS-GA based scheduling system is promising for practical job-shop scheduling.
最后，大量的仿真實驗證明了基于MAS和GA的車間調度系統在實際應用中的前景。
A dynamic and real-time system integrating reinforcement learning with simulation is designed for job-shop scheduling.
設計了一個強化學習和仿真相結合的動態實時車間作業排序系統。
In the introduction, it states the significance, recent actuality and research methods of job shop scheduling problem.
全文共分七個章節，首先在第一章緒論中論述了車間調度問題的重要性及其研究現狀、方法。
Firstly, a Flexible Job-shop Scheduling model under uncertain information environment is proposed in this thesis.
本文首先建立了不確定信息條件下的柔性作業車間調度模型。
Resource selection in job-shop scheduling has a direct influence on the product quality, date of delivery and production cost.
車間作業計劃中的資源選擇直接影響到產品的質量、交貨期和生產成本。
The whole frame of the scheduling system for the job shop scheduling of transformer with roll-core network manufacturing system is provided.
針對卷鐵芯變壓器網絡化制造車間的調度問題，給出了調度系統的整體框架，將這個網絡化制造系統分為兩層調度體系。
CIM differs from the traditional job shop manufacturing system in the role the computer plays in the manufacturing process.
CIM與傳統的加工車間的制造系統的區別在于計算機在制造過程中所起的作用。
Analyzing the model of the flexible job-shop scheduling problem(FJSP), an immune genetic algorithm(IGA) is proposed to solve the problem.
通過對柔性作業車間調度問題（FJSP）進行分析，借鑒生物免疫機理提出一種求解柔性作業車間調度問題的免疫遺傳算法（IGA）。
Four years' experience either in a production or job shop environment.
生產或車間作業四年工作經驗。
To overcome prematurity &of genetic algorithm, a new algorithm to solve job-shop scheduling was presented.
為了克服遺傳算法早熟和最優解較差的缺點，提出了求解作業車間調度問題的新方法。
The Job Shop Problem (JSP) is a key technology in manufacturing system, and the Q learning was used to realize it.
在制造業系統中車間調度是一項關鍵技術，可以用強化學習中的Q學習實現對車間作業的動態調度。
The purpose of this paper is using the algorithm to solve the dynamic Job shop scheduling problems.
在此基礎上，本文嘗試將縮短空閑時間法應用到多作業動態車間作業調度問題上。
Because there is much difficulty in processing in these two types of job shop scheduling, few optional algorithms are available.
由于這兩類車間調度問題存在高度的計算難處理性，因而可供選擇的算法比較少。
Several stochastic variables are introduced to transform the job-shop scheduling problem into sequential decision problem.
首先引入多個隨機變量，將車間作業排序問題轉換成序貫決策問題；
The second problem is the fuzzy flexible job shop scheduling problem with preventive maintenance.
第二類問題為具有預防性維修的模糊柔性作業車間調度問題。
A combination decision model of scheduling rules based on simulation is presented for multi-objective problems of job shop scheduling.
針對車間調度規則組合的多目標優化問題，提出了一種基于仿真的評估決策模型。
So, the paper researches on the mold enterprise's job shop scheduling problem.
為此，本文圍繞面向模具企業的車間作業調度問題展開研究。
This paper proposes a method of adaptive neural network based on constraint satisfaction for Job Shop Scheduling Problem.
提出一種基于約束滿足的自適應神經網絡方法求解車間作業調度問題。
The dramatic characteristic of the job shop scheduling problem is its complexity.
車間調度問題的突出特點是其復雜性。
The first problem is the fuzzy flexible job shop scheduling problem.
第一類問題為模糊柔性作業車間調度問題。
and finally proposed an improved ant colony algorithm applying to solve the job shop scheduling problem.
提出了一種改進的蟻群算法應用于解決車間調度問題。
Then, a multi-agent Q-learning algorithm integrated with simulation is developed to solve the job-shop problem.
體Q-學習算法和仿真集成解決作業排序問題；
Then the scheduling model combining monthly plan scheduling and re-scheduling is proposed based on the job-shop scheduling model.
并以調度模型為核心，設計并實現了某船廠的涂裝生產管理系統。
Facility layout of job shop problem is non-linear and NP-complete characteristic, and can not he solved well by conventional methods.
車間設備布局問題具有非線性、NP難等特性，無法運用傳統方法求得最優解。
It is difficult to get the absolute position of magnets because of obstacle in job-shop and this often causes trouble in debugging AGV.
車間環境障礙使得磁釘的絕對位置難以精確測量，給AGV的實際應用調試帶來不便。
The Job shop scheduling problem is a combinatorial optimum problem that is constrained with time, sequence and resource.
車間作業調度問題是一類具有時間約束、次序約束和資源約束的組合優化問題。
Performance Analysis of a Multi-objective Immune Genetic Algorithm and its Applications to Flexible Job Shop Scheduling
多目標免疫遺傳算法性能分析及其在柔性作業車間調度中的應用
Application of Particle Swarm Optimization with Adaptive Mutation to Job Shop Scheduling Problem and Its Software Implementation
基于自適應變異的粒子群優化算法的車間作業調度優化及其軟件實現
Adaptive Ant Colony Algorithm and Its Application to Multi-restriction Multi-Objective Flexible Job-Shop Scheduling
自適應蟻群算法及其在多約束多目標柔性Job-Shop調度中的應用
Study on the General Hybrid Genetic Algorithm for Job Shop Scheduling
求解作業排序問題的通用混合遺傳算法研究
Cooperative optimization algorithms used in job shop scheduling problem
作業車間調度問題中的協同優化算法
