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Scenario-Based Robust Remanufacturing Scheduling Problem Using Improved Biogeography-Based Optimization Algorithm

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DataCite Commons2021-02-21 更新2024-08-18 收录
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https://figshare.com/articles/dataset/Scenario-Based_Robust_Remanufacturing_Scheduling_Problem_Using_Improved_Biogeography-Based_Optimization_Algorithm/14069204
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This is the experimental data of the manuscript entitled “Scenario-Based Robust Remanufacturing Scheduling Problem Using Improved Biogeography-Based Optimization Algorithm ”. All data are generated through computer simulation and saved in the file with csv format. The first folder "1.SRRSP benchmark problem instances" includes 21SRRSP benchmark problem instances, the second folder "2.Additional data used to verify the practicability of considering multiple scenarios" contains the addition data required to demonstrate the practicability of considering multiple scenarios, the third folder "3.Additional data used to verify the practicability of variable start-up batch size constraint" contains the the addition data required to demonstrate the practicability of variable start-up batch size constraint. These datasets show the number of scenarios, the number of remanufacturing jobs, the number of operations for each job, the number of remanufacturing machines, the maximum batch size of batch processing machines, and the minimum batch size of batch processing machines. The value of variance factor, the probability of the occurrence of each scenario, the index of the batch processing machine, the index of the batch processing operation, the arrival time of each remanufacturing job, the set of machines available for each operation, and the processing time of each operation on the available machines are also shown in the datasets. And the fourth folder "4.The standard for generating the arrival time and processing time of EOL products in each scenario in each instances" contains the standard used to generate the arrival time and processing time of EOL products in each scenario in each instances.

本数据集对应题为《基于改进生物地理学优化算法的场景鲁棒再制造调度问题》的手稿实验数据。所有数据均通过计算机仿真生成,并以CSV格式文件存储。第一个文件夹“1.SRRSP基准算例(1.SRRSP benchmark problem instances)”包含21个SRRSP基准算例;第二个文件夹“2.验证多场景考量实用性的补充数据(2.Additional data used to verify the practicability of considering multiple scenarios)”收录用于论证多场景考量可行性的补充数据;第三个文件夹“3.验证可变启动批量约束实用性的补充数据(3.Additional data used to verify the practicability of variable start-up batch size constraint)”收录用于论证可变启动批量约束可行性的补充数据。本数据集涵盖场景数量、再制造作业数量、各作业的工序数量、再制造机床数量、批量加工机床的最大批量规模与最小批量规模。此外,数据集中还包含方差因子取值、各场景发生概率、批量加工机床索引、批量加工工序索引、各再制造作业的到达时间、各工序可用机床集合,以及各工序在对应可用机床上的加工时间。第四个文件夹“4.各算例中各场景下EOL产品(End-of-Life, EOL)到达时间与加工时间生成规范(4.The standard for generating the arrival time and processing time of EOL products in each scenario in each instances)”收录用于生成各算例中各场景下EOL产品到达时间与加工时间的相关规范。
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figshare
创建时间:
2021-02-21
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