CSPP instance

This Python script (<code>instance_generator.py</code>) is a tool designed to <b>programmatically generate synthetic instance data for container stowage and logistics problems.</b>Its primary function is to create structured datasets that simulate container terminal operations, which can then be used for developing, testing, and benchmarking optimization algorithms (e.g., for yard stacking strategies, vessel stowage planning).Key features and workflow include:<b>Parameterized Generation</b>: The script allows users to customize the generated data by specifying parameters such as:The total number of containers to create.The number of distinct attribute groups (simulating different container types, destinations, etc.).The configuration of the yard (number of areas, bay structure, rows, and levels).The configuration of the vessel (bay structure, rows, and tiers).<b>Data Initialization</b>:It internally creates a DataFrame to hold the instance data.Unique container numbers (<code>CNTR_NO</code>) are generated for each container.Containers are randomly assigned to different attribute groups (<code>attr_group_no</code>).<b>Yard Location Assignment</b>:The script systematically assigns each container a specific location in the simulated yard, including <code>area_no</code>, <code>area_bay</code>, <code>area_row</code>, and <code>area_level</code>.It also generates a standardized yard location code (<code>VPC_VLOCATION</code>) for each container.<b>Vessel Location Assignment</b>:Containers are assigned target locations on a simulated vessel (<code>ship_bay</code>, <code>ship_row</code>, <code>ship_tie</code>).This assignment is typically based on the container's attribute group, ensuring that similar containers are often grouped together on the vessel.It also sets related flags like <code>is_in_cabin</code> (indicating if the container is in the hold or on deck).<b>Direct Execution</b>: The script is set up to run directly. When executed, it uses a predefined set of parameters (which can be easily modified within the script) to generate an instance and can save this data to a CSV file (e.g., <code>generated_stowage_instance_direct.csv</code>).

本Python脚本（<code>instance_generator.py</code>）是一款专为集装箱积载与物流问题**程序化生成合成实例数据**的工具。其核心功能为构建模拟集装箱码头作业的结构化数据集，可用于开发、测试与优化算法的性能基准测试（例如堆场堆存策略、船舶积载规划相关算法）。
核心特性与工作流程如下：
**参数化生成**：该脚本支持用户通过指定以下参数自定义生成的数据：
- 待生成集装箱的总数量
- 不同属性组的数量（用于模拟不同集装箱类型、目的地等场景）
- 堆场配置信息（包括堆场区域数量、箱区结构、箱列数与堆层数）
- 船舶配置信息（包括箱区结构、箱列数与舱位层数）
**数据初始化**：脚本内部会创建用于存储实例数据的数据框（DataFrame），为每个集装箱生成唯一的集装箱编号（<code>CNTR_NO</code>），并将集装箱随机分配至不同的属性组（<code>attr_group_no</code>）。
**堆场位置分配**：脚本会为每个集装箱系统分配模拟堆场中的具体位置，包括<code>area_no</code>（堆场区域编号）、<code>area_bay</code>（堆场箱区号）、<code>area_row</code>（堆场箱列号）与<code>area_level</code>（堆场堆层号），同时为每个集装箱生成标准化的堆场位置编码（<code>VPC_VLOCATION</code>）。
**船舶位置分配**：为集装箱分配模拟船舶上的目标装载位置（<code>ship_bay</code>、<code>ship_row</code>、<code>ship_tie</code>），该分配过程通常基于集装箱所属的属性组进行，可确保同类集装箱在船舶上的装载位置相对集中，同时会设置相关标识字段，例如<code>is_in_cabin</code>（用于标识集装箱位于舱内还是甲板上）。
**直接运行模式**：该脚本支持直接执行。运行时，脚本将使用预设的参数集（用户可在脚本内轻松修改该参数集）生成实例数据，并可将数据保存至CSV文件（例如<code>generated_stowage_instance_direct.csv</code>）。