Computational Experiment Results for the Job Shop Scheduling Problem with Time Lags (JSPTL)

This dataset contains the results of computational experiments conducted on benchmark instances of the Job Shop Scheduling Problem with Time Lags (JSPTL). The table compares the performance of different algorithms, including:
- MA: Memetic Algorithm (Caumond et al., 2008)
- SSPR: Shifting Bottleneck Procedure with Simulated Annealing (Gonzalez et al., 2015)
- This paper: Proposed approach from the current study.
Metrics include:
- GAP (%): Gap between the solution and the optimal/known best lower bound.
- t (s): Computational time in seconds.
The dataset is divided into two parts:
- Instances with small to medium complexity (la01 to la05), with averages provided.
- Instances with higher complexity (la06 to la08), with corresponding averages.
This data supports the analysis of the efficiency and competitiveness of the proposed method in comparison to state-of-the-art algorithms.

本数据集收录了在具有时间延迟的作业车间调度问题（JSPTL）基准实例上进行的计算实验结果。该表格对比了包括以下算法的性能：
- MA：遗传算法（Caumond 等，2008年）
- SSPR：带模拟退火算法的瓶颈移位过程（Gonzalez 等，2015年）
- 本研究方法：当前研究提出的方案。
评价指标包括：
- GAP（%）：解与最优/已知的最佳下界之间的差距。
- t（秒）：计算时间，单位为秒。
数据集分为两部分：
- 复杂度从小到中等（la01 至 la05）的实例，并提供平均值。
- 复杂度较高的实例（la06 至 la08），并附上相应的平均值。
本数据支持对所提出方法在效率与竞争力方面的分析，与现有最先进算法进行比较。