Random processing times for scenarios with different number of sequential machines with different variations between pair of machines
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<b>Description:</b>This random scenarios were generated by applying a normal distribution for processing time of machine 1 (p1). From p2 to pn (processing time of machine n), it was made a random variation up to more or less 20, 50 and 70% from the processing time of the previous machine. Further, the number of machines can be 5, 10 or 15.<br><b>Legend of the files names:</b>[number of machines][number of variation]_Scenarios.xlsxExample:- 0520_Scenarios.xlsx-- Scenarios with 05 machines with 20% of variation- 1550_Scenarios.xlsx-- Scenarios with 15 machines with 50% of variation<br><br><b>Legend of the files colums:</b>- First column is the number of the random scenario;- p1, p2, p3, ..., pn - refers to the processing time of the machine 1, 2, 3, ..., n.- peq - refers to an equivalent processing time, calculated according to [1].- U - number of items to be processed in the machines.<br>[1] da Silva, Ramon Gomes. (2019). Proposição de uma teoria empírica para estimativa de capacidade utilizando as técnicas de lot streaming. [Portuguese][Proposition of an empirical theory for capacity estimation using lot streaming techniques] (Unpublished master's thesis). Pontifical Catholic University of Parana, Curitiba, Brazil. doi:10.13140/RG.2.2.28913.12640. <br>
<b>数据集描述：</b>本随机场景通过为机器1（记为p1）的加工时间（processing time）设置正态分布（normal distribution）生成。对于机器2至机器n（记为p2至pn）的加工时间，其取值在对应前序机器加工时间的±20%、±50%与±70%范围内随机波动。此外，机器数量可设置为5、10或15。<br><b>文件名命名规则：</b>文件名格式为：[机器数量][波动幅度]_Scenarios.xlsx。示例：<br>- 0520_Scenarios.xlsx：代表包含5台机器且加工时间波动幅度为20%的场景数据集；<br>- 1550_Scenarios.xlsx：代表包含15台机器且加工时间波动幅度为50%的场景数据集。<br><br><b>文件列名说明：</b><br>- 第一列为随机场景的编号；<br>- p1、p2、p3、……、pn：分别对应机器1、2、3、……、n的加工时间；<br>- peq：指代等效加工时间（equivalent processing time），计算依据参见文献[1]；<br>- U：表示需在各机器上加工的工件总数。<br><br>[1] da Silva, Ramon Gomes. (2019). 采用批量流技术（lot streaming）的产能估算实证理论构建[原文为葡萄牙语][Proposition of an empirical theory for capacity estimation using lot streaming techniques]（未发表硕士学位论文）. 巴西巴拉那天主教大学，库里提巴。doi:10.13140/RG.2.2.28913.12640.
