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Efficiency-aware parallel machine scheduling with machine and server selection: MILP models and a matheuristic algorithm
DOI:10.1016/j.cie.2026.112249.png)
摘要
En 中文
• 首次研究了集成机器和服务器选择与调度问题。
• 目标是最小化总完成时间、机器数量和服务器数量。
• 开发了基于时间索引和基于序列索引的 MILP 模型。
• 提出了一种基于 ALNS 的数学启发式算法。
• 该数学启发式算法将时间索引模型改进了 40%,将基于序列索引的模型改进了 36%。
期刊
C
IF:
6.5
论文数:
567
被引数:
0
机构
引用论文
The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm
Mathematics
IF0
Uniform Parallel Machine Scheduling with Dedicated Machines, Job Splitting and Setup Resources
SUSTAINABILITY
IF3.3
A note on Self-adaptive General Variable Neighborhood Search algorithm for parallel machine scheduling with unrelated servers关于非相关服务器并行机调度中自适应性广义变量邻域搜索算法的注记
Minimization of maximum lateness on parallel machines with a single server and job release dates在具有单服务器和作业发布时间的并行机上的最大延迟最小化
4OR
IF0
General variable neighborhood search for the parallel machine scheduling problem with two common servers通用变邻域搜索算法在具有两个通用服务器的并行机器调度问题中的应用

