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To efficiently solve this problem, we propose a hybrid evolutionary algorithm, which adapts the water wave optimization (WWO) metaheuristic to evolve solutions to the main order selection problem and employs tabu search to route the delivery path for each order selection solution. Experimental results on test instances constructed based on real food delivery application data demonstrate the performance advantages of the proposed algorithm compared to a set of popular metaheuristic optimization algorithms.<\/jats:p>","DOI":"10.1007\/s40747-021-00410-0","type":"journal-article","created":{"date-parts":[[2021,6,2]],"date-time":"2021-06-02T19:42:33Z","timestamp":1622662953000},"page":"4425-4440","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Hybrid evolutionary optimization for takeaway order selection and delivery path planning utilizing habit data"],"prefix":"10.1007","volume":"8","author":[{"given":"Min-Xia","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Jia-Yu","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Xue","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6095-6325","authenticated-orcid":false,"given":"Yu-Jun","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,2]]},"reference":[{"issue":"5","key":"410_CR1","doi-asserted-by":"publisher","first-page":"1693","DOI":"10.1016\/j.cor.2008.04.003","volume":"36","author":"TJ Ai","year":"2009","unstructured":"Ai TJ, Kachitvichyanukul V (2009) A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. 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