本数据集面向旅游路线规划问题，旨在为旅游路线规划算法的性能评估提供核心数据支撑。数据集以纯文本文件形式存储，首行记录着用户的起点信息，行数代表了景点的数量。数据中，第一列是景点的横坐标x，第二列是景点的纵坐标y，这两列共同构成景点的坐标信息；第三列表示该景点的体验值得分；第四列则为景点的门票价格，各数据项之间以空格作为分隔。其中，景点的旅游体验值在区间[1, 10]内随机生成，景点门票价格在[10, 150]区间随机产生。
", "ds_source": "本数据集为完全仿真生成数据，不源自特定文献、实测或第三方下载
", "ds_process_way": "本数据集基于仿真生成方式构建，其生成过程基于Python开源包Numpy。具体而言，在原OP数据集基础上（下载地址：https://github.com/bcamath-ds/OPLib/blob/master/instances/gen2/kroA100-gen2-50.oplib），保持第一列景点横坐标x和第二列景点纵坐标y不变，利用Numpy在区间[1, 10]内随机生成景点的旅游体验值，在[10, 150]区间随机产生景点门票价格。
", "ds_quality": "本数据集在生成和汇集过程中实施了系统性质量控制，确保了数据的完整性、准确性和代表性。
", "ds_acq_start_time": "2024-01-01 00:00:00", "ds_acq_end_time": null, "ds_acq_place": "南京", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 94185, "ds_files_count": 0, "ds_format": "txt", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "e1134474-f5e2-4fed-b0a6-741ad4e6baa6.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": "", "organization_id": "9ecaaa78-39e9-411e-9f24-274e12aa643f", "ds_serv_man": "杨强", "ds_serv_phone": "13570466708", "ds_serv_mail": "mmmyq@126.com", "doi_value": "", "subject_codes": [ "410" ], "quality_level": 0, "publish_time": "2026-07-09 10:57:45", "last_updated": "2026-07-09 10:57:45", "protected": false, "protected_to": "2028-06-30 00:00:00", "lang": "zh", "cstr": "", "i18n": { "en": { "title": "Tourism Route Planning Simulation Dataset", "ds_format": "txt", "ds_source": "This dataset is completely synthetically generated through simulation and does not originate from specific literature, field measurements, or third-party downloads.", "ds_quality": "During the generation and collection of this dataset, systematic quality control measures were implemented to ensure its completeness, accuracy, and representativeness.", "ds_ref_way": "", "ds_abstract": "This dataset is designed for tourism route planning problems and aims to provide core data support for evaluating the performance of tourism route planning algorithms. The dataset is stored in plain text format, with the first line recording the user's starting point, and each subsequent line corresponding to a tourist attraction — the total number of lines indicating the number of attractions. Each line contains four fields: the first two columns represent the attraction's coordinates (x and y), the third column represents the attraction's experience score (randomly generated within the interval [1,10]), and the fourth column represents the ticket price (randomly generated within the interval [10,150]). The fields are separated by spaces.", "ds_time_res": "", "ds_acq_place": "Nanjing", "ds_space_res": "", "ds_projection": "", "ds_process_way": "This dataset is constructed through simulation generation, with the process based on the Python open-source package NumPy. Specifically, building upon the original OP dataset (available at: https://github.com/bcamath-ds/OPLib/blob/master/instances/gen2/kroA100-gen2-50.oplib), we retain the first column (x-coordinate) and the second column (y-coordinate) of each attraction unchanged. We then utilize NumPy to randomly generate the tourism experience value for each attraction within the interval [1, 10], and randomly generate the ticket price within the interval [10, 150].", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "路线规划", "智慧旅行", "群智优化" ], "ds_subject_tags": [ "工程与技术科学基础学科" ], "ds_class_tags": [], "ds_locus_tags": [], "ds_time_tags": [], "ds_contributors": [ { "true_name": "杨强", "email": "mmmyq@126.com", "work_for": "南京信息工程大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "杨强", "email": "mmmyq@126.com", "work_for": "南京信息工程大学", "country": "中国" }, { "true_name": "陆振宇", "email": "luzhenyu76@163.com", "work_for": "南京信息工程大学人工智能学院（未来技术学院）", "country": "中国" } ], "ds_managers": [ { "true_name": "杨强", "email": "mmmyq@126.com", "work_for": "南京信息工程大学", "country": "中国" } ], "category": "其他" }