{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T02:23:58Z","timestamp":1783650238553,"version":"3.55.0"},"reference-count":39,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The proper vehicle-route selection is a key challenge affecting the quality of urban logistics since any delay may cause disasters. This study proposes a novel approach of using symmetry\/asymmetry traffic context data and multi-criteria decision analysis to optimize vehicle-route selection as part of urban-logistical planning. The traffic context data are collected from official urban transportation databases and metadata of Google Maps route planning to construct a context-based social network. The traffic features and routing criteria have symmetry\/asymmetry properties to influence the decision of path selection. Multi-criteria decision analysis can generate a ranking of candidate paths based on an evaluation of traffic data in context-based social networks to recommend to the deliveryman. The deliveryman can select a reasonable path for delivering products according to the ranking of candidate paths. A case study demonstrates the steps of the proposed approach. Experimental results show that the precision is 79.65%, recall is 80.70%, and F1-score is 80.17%, thus proving the vehicle-route recommendation effectiveness. The contribution of this work is to optimize traffic-routing solutions for improved urban logistics in smart cities. It helps deliverymen send products as soon as possible to customers to retain quality, especially in cold-chain logistics.<\/jats:p>","DOI":"10.3390\/sym14091811","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:19:01Z","timestamp":1662077941000},"page":"1811","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Optimizing the Routing of Urban Logistics by Context-Based Social Network and Multi-Criteria Decision Analysis"],"prefix":"10.3390","volume":"14","author":[{"given":"Mei-Yu","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Business Management, National Taichung University of Science and Technology, 129, Sec. 3, Sanmin Rd., North District, Taichung 404, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0753-1624","authenticated-orcid":false,"given":"Chih-Kun","family":"Ke","sequence":"additional","affiliation":[{"name":"Department of Information Management, National Taichung University of Science and Technology, 129, Sec. 3, Sanmin Rd., North District, Taichung 404, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Szu-Cheng","family":"Lai","sequence":"additional","affiliation":[{"name":"Department of Information Management, National Taichung University of Science and Technology, 129, Sec. 3, Sanmin Rd., North District, Taichung 404, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1023\/A:1009804230409","article-title":"E-commerce recommendation applications","volume":"5","author":"Schafer","year":"2001","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1145\/345124.345165","article-title":"Personalization on the Net using Web mining: Introduction","volume":"43","author":"Mulvenna","year":"2000","journal-title":"Commun. ACM"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1007\/s00607-015-0448-7","article-title":"A survey on context-aware recommender systems based on computational intelligence techniques","volume":"97","author":"Abbas","year":"2015","journal-title":"Computing"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wei, L.Y., Zheng, Y., and Peng, W.C. (2012, January 12\u201316). Constructing popular routes from uncertain trajectories. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, China.","DOI":"10.1145\/2339530.2339562"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1016\/j.ejor.2012.11.059","article-title":"A memetic algorithm for the multiperiod vehicle routing problem with profit","volume":"229","author":"Zhang","year":"2013","journal-title":"Eur. J. Oper. Res."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Liu, B., and Xiong, H. (2013, January 2\u20134). Point-of-Interest recommendation in location based social networks with topic and location awareness. Proceedings of the 2013 Siam International Conference on Data Mining (SDM), Austin, TX, USA.","DOI":"10.1137\/1.9781611972832.44"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"7370","DOI":"10.1016\/j.eswa.2014.06.007","article-title":"Intelligent tourism recommender systems: A survey","volume":"41","author":"Borris","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1007\/s10707-014-0220-8","article-title":"Recommendations in location-based social net-works: A survey","volume":"19","author":"Bao","year":"2015","journal-title":"GeoInformatica"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1109\/TKDE.2014.2362525","article-title":"A general geographical probabilistic factor model for point of interest recommendation","volume":"27","author":"Liu","year":"2014","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_10","unstructured":"Sheng, l.Z., Irwin, K., and Michael, R.L. (2016). A survey of Point-of-interest Recommendation in Location-based social network. arXiv."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ishizaka, A., and Nemery, P. (2013). Multi-Criteria Decision Analysis: Methods and Software, Wiley.","DOI":"10.1002\/9781118644898"},{"key":"ref_12","first-page":"31","article-title":"A survey on multi criteria decision making methods and its applications","volume":"1","author":"Aruldoss","year":"2013","journal-title":"Am. J. Inf. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"114593","DOI":"10.1016\/j.eswa.2021.114593","article-title":"A POI group recommendation method in location-based social networks based on user influence","volume":"171","author":"Sojahrood","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Pablo, S., and Alejandro, B. (2022). Point-of-interest recommender systems based on location-based social networks: A survey from an experimental perspective. ACM Comput. Surv., 1\u201335.","DOI":"10.1145\/3510409"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wang, Z.S., Juang, J.F., and Teng, W.G. (2015, January 20\u201322). Predicting poi visits with a heterogeneous information network. Proceedings of the 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI), IEEE, Tainan, Taiwan.","DOI":"10.1109\/TAAI.2015.7407077"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1109\/THMS.2015.2446953","article-title":"Personalized travel package with multi-point-of-interest recommendation based on crowdsourced user footprints","volume":"46","author":"Yu","year":"2016","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"188","DOI":"10.3390\/info13040188","article-title":"Recommendation system algorithms on location-based social networks: Comparative study","volume":"13","author":"Abeer","year":"2022","journal-title":"Information"},{"key":"ref_18","unstructured":"Ke, C.K., Lai, S.C., and Huang, L.T. (2018, January 15\u201316). Developing a Context-aware POI Network of Adaptive Vehicular Traffic Routing for Urban Logistics. Proceedings of the 11th EAI International Wireless Internet Conference (WiCON 2018), Taipei, Taiwan."},{"key":"ref_19","unstructured":"Ke, C.K., Wu, M.Y., Ho, W.C., Lai, S.C., and Huang, L.T. (2018, January 26\u201330). Intelligent Point-of-Interest Recommendation for Tourism Planning via Density-based Clustering and Genetic Algorithm. Proceedings of the 22nd Pacific Asia Conference on Information Systems (PACIS 2018), Yokohama, Japan."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.tra.2017.10.013","article-title":"An integrated MCDM approach to evaluate public transportation systems in Tehran","volume":"106","author":"Nassereddine","year":"2017","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Safavi, S., Jalali, M., and Houshmand, M. (2022). Toward point-of-interest recommendation systems: A critical review on deep-learning Approaches. Electronics, 11.","DOI":"10.3390\/electronics11131998"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Griesner, J.B., Abdessalem, T., and Naacke, H. (2015, January 16\u201320). POI Recommendation: Towards Fused Matrix Factorization with Geographical and Temporal Influences. Proceedings of the 9th ACM Conference on Recommender Systems, Vienna, Austria.","DOI":"10.1145\/2792838.2799679"},{"key":"ref_23","unstructured":"Cheng, C., Yang, H.Q., Lyu, M.R., and King, I. (2015, January 25\u201331). Where You Like to Go Next: Successive Point-of-Interest Recommendation. Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina."},{"key":"ref_24","unstructured":"Feng, S.S., Li, X.T., Zeng, Y.F., Cong, G., Chee, Y.M., and Yuan, Q. (2015, January 25\u201331). Personalized Ranking Metric Embedding for Next New POI Recommendation. Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Han, J.K., and Yamana, H. (2017, January 27\u201331). Geographical Diversification in POI Recommendation: Toward Improved Coverage on Interested Areas. Proceedings of the ACM Conference Series on Recommender Systems, Como, Italy.","DOI":"10.1145\/3109859.3109884"},{"key":"ref_26","unstructured":"Liu, X., Liu, Y., and Aberer, K. (November, January 27). Personalized Point-of-Interest Recommendation by Mining Users\u2019 Preference Transition. Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, San Francisco, CA, USA."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.neucom.2021.11.049","article-title":"TransMKR: Translation-based knowledge graph enhanced multi-task point-of-interest recommendation","volume":"474","author":"Hu","year":"2022","journal-title":"Neurocomputing"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"117700","DOI":"10.1016\/j.eswa.2022.117700","article-title":"The role of context fusion on accuracy, beyond-accuracy, and fairness of point-of-interest recommendation systems","volume":"205","author":"Hossein","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.neucom.2021.09.056","article-title":"Real-time POI recommendation via modeling long- and short-term user preferences","volume":"467","author":"Liu","year":"2022","journal-title":"Neurocomputing"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1016\/j.asoc.2011.08.046","article-title":"Identifying and eliminating dominated alternatives in multi-attribute decision making with intuitionistic fuzzy information","volume":"12","author":"Xu","year":"2012","journal-title":"Appl. Soft Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3755","DOI":"10.1016\/j.eswa.2009.11.048","article-title":"Developing a hybrid multi-criteria model for selection of outsourcing providers","volume":"37","author":"Liou","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"8112","DOI":"10.1016\/j.eswa.2014.07.021","article-title":"A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection","volume":"41","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_33","first-page":"95","article-title":"Improving metro\u2013airport connection service for tourism development: Using hybrid MCDM models","volume":"6","author":"Liu","year":"2013","journal-title":"Tour. Manag. Perspect."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1016\/j.camwa.2012.03.024","article-title":"A message negotiation approach to e-services by utility function and multi-criteria decision analysis","volume":"64","author":"Ke","year":"2012","journal-title":"Comput. Math. Appl."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.compeleceng.2016.01.018","article-title":"Optimal mobile device selection for round-robin data exchange via adaptive multi-criteria decision analysis","volume":"54","author":"Chen","year":"2016","journal-title":"Comput. Electr. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Silaghi, G.C., Arenas, A.E., and Silva, L.M. (2007). A Utility-Based Reputation Model for Service-Oriented Computing, towards Next Generation Grids, Springer.","DOI":"10.1007\/978-0-387-72498-0_6"},{"key":"ref_37","unstructured":"Chen, M.C. (2016). A Comparative Study of Multi-Criteria Decision-Making Analysis Methods in the Application Recommendation Mechanism of Application Markets. [Master\u2019s Thesis, National Taichung University of Science and Technology]."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.knosys.2013.04.007","article-title":"Integrating semantic Web services ranking mechanisms using a common preference model","volume":"49","author":"Junghans","year":"2013","journal-title":"Knowl.-Based Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.jss.2014.01.036","article-title":"A trustworthy QoS-based collaborative filtering approach for web service discovery","volume":"93","author":"Lin","year":"2014","journal-title":"J. Syst. Softw."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/14\/9\/1811\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:21:37Z","timestamp":1760142097000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/14\/9\/1811"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,1]]},"references-count":39,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["sym14091811"],"URL":"https:\/\/doi.org\/10.3390\/sym14091811","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,1]]}}}