{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T05:50:30Z","timestamp":1773726630930,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T00:00:00Z","timestamp":1716768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Information Technology Academia Collaboration (ITAC)","award":["CFP227"],"award-info":[{"award-number":["CFP227"]}]},{"name":"Nile University","award":["CFP227"],"award-info":[{"award-number":["CFP227"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Environmental concerns have called for several measures to be taken within the logistics and transportation fields. Among these measures is the adoption of electric vehicles instead of diesel-operated vehicles for personal and commercial-delivery use. The optimized routing of electric vehicles for the commercial delivery of products is the focus of this paper. We study the effect of several practical challenges that are faced when routing electric vehicles. Electric vehicle routing faces the additional challenge of the potential need for recharging while en route, leading to more travel time, and hence cost. Therefore, in this work, we address the issue of electric vehicle routing problem, allowing for partial recharging while en route. In addition, the practical mandate of the time windows set by customers is also considered, where electric vehicle routing problems with soft time windows are studied. Real-life experience shows that the delivery of customers\u2019 demands might be uncertain. In addition, real-time traffic conditions are usually uncertain due to congestion. Therefore, in this work, uncertainties in customers\u2019 demands and traffic conditions are modeled and solved using fuzzy methods. The problems of fuzzy real-time, fuzzy demand, and electric vehicle routing problems with soft time windows are addressed. A mixed-integer programming mathematical model to represent the problem is developed. A novel two-phase solution approach is proposed to solve the problem. In phase I, the classical genetic algorithm (GA) is utilized to obtain an optimum\/near-optimum solution for the fuzzy demand electric vehicle routing problem with soft time windows (FD-EVRPSTW). In phase II, a novel fuzzy real-time-adaptive optimizer (FRTAO) is developed to overcome the challenges of recharging and real-time traffic conditions facing FD-EVRPSTW. The proposed solution approach is tested on several modified benchmark instances, and the results show the significance of recharging and congestion challenges for routing costs. In addition, the results show the efficiency of the proposed two-phase approach in overcoming the challenges and reducing the total costs.<\/jats:p>","DOI":"10.3390\/computers13060135","type":"journal-article","created":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T10:12:27Z","timestamp":1716804747000},"page":"135","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Two-Phase Fuzzy Real-Time Approach for Fuzzy Demand Electric Vehicle Routing Problem with Soft Time Windows"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4942-9257","authenticated-orcid":false,"given":"Mohamed A. Wahby","family":"Shalaby","sequence":"first","affiliation":[{"name":"Smart Engineering Research Center, Nile University, Giza 12677, Egypt"},{"name":"Faculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sally S.","family":"Kassem","sequence":"additional","affiliation":[{"name":"Faculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, Egypt"},{"name":"Smart Engineering Research Center, Nile University, Giza 12677, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1287\/mnsc.6.1.80","article-title":"The Truck Dispatching Problem","volume":"6","author":"Dantzig","year":"1959","journal-title":"Manag. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kassem, S., Korayem, L., Khorshid, M., and Tharwat, A. (2019, January 28\u201330). A hybrid bat algorithm to solve the capacitated vehicle routing problem. Proceedings of the 2019 Novel Intelligent and Leading Emerging Sciences Conference (NILES), Giza, Egypt.","DOI":"10.1109\/NILES.2019.8909300"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1287\/trsc.31.4.372","article-title":"An Exact Algorithm for the Vehicle Routing Problem with Backhauls","volume":"31","author":"Toth","year":"1997","journal-title":"Transp. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"108044","DOI":"10.1016\/j.cie.2022.108044","article-title":"A learning enhanced golden ball algorithm for the vehicle routing problem with backhauls and time windows","volume":"168","author":"Worawattawechai","year":"2022","journal-title":"Comput. Ind. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106571","DOI":"10.1016\/j.cie.2020.106571","article-title":"Hybrid differential evolution algorithm and genetic operator for multi-trip vehicle routing problem with backhauls and heterogeneous fleet in the beverage logistics industry","volume":"146","author":"Sethanan","year":"2020","journal-title":"Comput. Ind. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1287\/opre.35.2.254","article-title":"Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints","volume":"35","author":"Solomon","year":"1987","journal-title":"Oper. Res."},{"key":"ref_7","first-page":"909","article-title":"A Heterogeneous Vehicle Routing Problem with Soft Time Windows for 3PL Company\u2019s Deliveries: A Case Study","volume":"54","author":"Ismail","year":"2021","journal-title":"J. Eur. Des Syst. Autom."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.tre.2005.01.003","article-title":"The real-time time-dependent vehicle routing problem","volume":"42","author":"Chen","year":"2006","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_9","first-page":"59","article-title":"Vehicle routing problem with real-time travel times","volume":"2","author":"Okhrin","year":"2009","journal-title":"Int. J. Veh. Inf. Commun. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"103379","DOI":"10.1016\/j.trc.2021.103379","article-title":"Managing in real-time a vehicle routing plan with time-dependent travel times on a road network","volume":"132","author":"Gmira","year":"2021","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1287\/trsc.2013.0490","article-title":"The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations","volume":"48","author":"Schneider","year":"2014","journal-title":"Transp. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yu, V.F., Anh, P.T., and Chen, Y.-W. (2023). The Electric Vehicle Routing Problem with Time Windows, Partial Recharges, and Parcel Lockers. Appl. Sci., 13.","DOI":"10.3390\/app13169190"},{"key":"ref_13","first-page":"1","article-title":"Mathematical models for the electric vehicle routing problem with time windows considering different aspects of the charging process","volume":"24","author":"Linfati","year":"2024","journal-title":"Oper. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"6178","DOI":"10.1109\/TITS.2023.3249403","article-title":"Electric Vehicle Routing Problem with Variable Vehicle Speed and Soft Time Windows for Perishable Product Delivery","volume":"24","author":"Liu","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Hao, S. (2021, January 20\u201322). Electric Vehicle Routing Problem with Soft Time Window and Weight-related Discharging Using Adaptive Large-Scale Neighborhood Search Algorithm. Proceedings of the 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT), Changsha, China.","DOI":"10.1109\/ICCASIT53235.2021.9633428"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Xu, J., Cooke, F., Gen, M., and Ahmed, S. (2019). Proceedings of the Twelfth International Conference on Management Science and Engineering Management (ICMSEM 2018), Springer.","DOI":"10.1007\/978-3-319-93351-1"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5098183","DOI":"10.1155\/2017\/5098183","article-title":"Electric Vehicle Routing Problem with Charging Time and Variable Travel Time","volume":"2017","author":"Shao","year":"2017","journal-title":"Math. Probl. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1051\/ro\/2023006","article-title":"A heterogeneous electric taxi fleet routing problem with recharging stations to maximize the company\u2019s profit","volume":"57","author":"Nafarieh","year":"2023","journal-title":"RAIRO-Oper. Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, L., Li, T., Wang, K., Gao, S., Chen, Z., and Wang, L. (2019, January 13\u201315). Heterogeneous fleet electric vehicle routing optimization for logistic distribution with time windows and simultaneous pick-up and delivery service. Proceedings of the 2019 16th International Conference on Service Systems and Service Management (ICSSSM), Shenzhen, China.","DOI":"10.1109\/ICSSSM.2019.8887631"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"113123","DOI":"10.1016\/j.eswa.2019.113123","article-title":"Fuzzy optimization model for electric vehicle routing problem with time windows and recharging stations","volume":"145","author":"Zhang","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3030197","DOI":"10.1155\/2020\/3030197","article-title":"Time-Dependent Electric Vehicle Routing Problem with Time Windows and Path Flexibility","volume":"2020","author":"Wang","year":"2020","journal-title":"J. Adv. Transp."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"107650","DOI":"10.1016\/j.cie.2021.107650","article-title":"The electric vehicle routing problem and its variations: A literature review","volume":"161","author":"Dewil","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.cie.2011.10.001","article-title":"Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm","volume":"62","author":"Moghaddam","year":"2012","journal-title":"Comput. Ind. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"18","DOI":"10.23919\/CSMS.2022.0005","article-title":"Robust Electric Vehicle Routing Problem with Time Windows under Demand Uncertainty and Weight-Related Energy Consumption","volume":"2","author":"Shen","year":"2022","journal-title":"Complex Syst. Model. Simul."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1007\/s11067-013-9190-x","article-title":"A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service","volume":"13","author":"Zhang","year":"2013","journal-title":"Networks Spat. Econ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.trb.2019.06.006","article-title":"The electric vehicle routing problem with energy consumption uncertainty","volume":"126","author":"Pelletier","year":"2019","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/0165-0114(95)00276-6","article-title":"The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain","volume":"82","year":"1996","journal-title":"Fuzzy Sets Syst."},{"key":"ref_28","unstructured":"Lu\u010di\u0107, P., and Teodorovi\u0107, D. (2003). Fuzzy Sets Based Heuristics for Optimization, Springer."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.cam.2009.02.015","article-title":"A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands","volume":"231","author":"Erbao","year":"2009","journal-title":"J. Comput. Appl. Math."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Mu\u00f1oz, C.C., Palacios-Alonso, J.J., Vela, C.R., and Afsar, S. (2022, January 18\u201323). Solving a Vehicle Routing Problem with uncertain demands and adaptive credibility thresholds. Proceedings of the 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy.","DOI":"10.1109\/FUZZ-IEEE55066.2022.9882650"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Yang, T., Wang, W., and Wu, Q. (2022). Fuzzy Demand Vehicle Routing Problem with Soft Time Windows. Sustainability, 14.","DOI":"10.3390\/su14095658"},{"key":"ref_32","unstructured":"Shalaby, M.A.W., Mohammed, A.R., and Kassem, S. (2020, January 28\u201330). Modified Fuzzy C-Means Clustering Approach to Solve the Capacitated Vehicle Routing Problem. Proceedings of the 21st International Arab Conference on Information Technology (ACIT), Giza, Egypt."},{"key":"ref_33","first-page":"452","article-title":"Supervised Fuzzy C-Means Techniques to Solve the Capacitated Vehicle Routing Problem","volume":"18","author":"Shalaby","year":"2021","journal-title":"Int. Arab. J. Inf. Technol."},{"key":"ref_34","first-page":"8514660","article-title":"Solving Capacitated Vehicle Routing Problem by an Improved Genetic Algorithm with Fuzzy C-Means Clustering","volume":"2022","author":"Zhu","year":"2022","journal-title":"Sci. Program."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"205","DOI":"10.15294\/jaist.v4i2.62314","article-title":"Electric Vehicle Routing Problem with Fuzzy Time Windows using Genetic Algorithm and Tabu Search","volume":"4","author":"Syafrizal","year":"2023","journal-title":"J. Adv. Inf. Syst. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/j.trpro.2014.10.026","article-title":"Electric Vehicle Routing Problem with Industry Constraints: Trends and Insights for Future Research","volume":"3","author":"Afroditi","year":"2014","journal-title":"Transp. Res. Procedia"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Zhenfeng, G., Yang, L., Xiaodan, J., and Sheng, G. (2017, January 25\u201326). The electric vehicle routing problem with time windows using genetic algorithm. Proceedings of the 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, China.","DOI":"10.1109\/IAEAC.2017.8054093"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Mavrovouniotis, M., Ellinas, G., and Polycarpou, M. (2018, January 18\u201321). Ant Colony optimization for the Electric Vehicle Routing Problem. Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (SSCI), Bangalore, India.","DOI":"10.1109\/SSCI.2018.8628831"}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/13\/6\/135\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:49:02Z","timestamp":1760107742000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/13\/6\/135"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,27]]},"references-count":38,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["computers13060135"],"URL":"https:\/\/doi.org\/10.3390\/computers13060135","relation":{},"ISSN":["2073-431X"],"issn-type":[{"value":"2073-431X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,27]]}}}