As a popular research realm in manufacture system, Job Shop Scheduling is one of the most difficult problems in theoretic.
作业车间调度是制造系统的一个研究热点，也是理论研究中最为困难的问题之一。
While applied to Job Shop scheduling Problems, it has some limitations to be solved.
但在解决单件车间作业计划问题时，仍存在一些局限。
However, this way of introducing MES to strengthen job-shop scheduling and improve the running efficiency of plans faces many problems in the process.
然而，这种通过引入MES来加强车间级的生产计划调度、提高中长期计划的运行效率的方法在实际实施过程中遇到了很多问题。
In this paper, we propose an improved Lagrangian relaxation algorithm to solve job shop scheduling problems.
针对车间调度问题，提出了一种改进的拉氏松弛算法。
Job shop scheduling problem is one of the typical combinatorial optimization problems with constraints. To get its encoding has always been one of the main and difficult points of the problem.
车间作业调度问题是一类带有约束的典型的组合优化问题，目前采用人工鱼群算法解决车间作业调度问题没有检索到参考文献。
In order to solve NP - shop scheduling combinatorial optimization problems, an immune forgotten algorithm for job shop scheduling is proposed.
为了解决车间调度NP组合优化的难题，提出了基于免疫遗忘的车间调度算法。
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。
This paper considers the open shop scheduling problems with job priorities and release times.
讨论了工件准备时间、加工时间和交货期都为随机变量的单机调度问题。
This paper considers the open shop scheduling problems with job priorities and release times.
讨论了工件准备时间、加工时间和交货期都为随机变量的单机调度问题。
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