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When a wildebeest wants to choose its path during migration, it considers the best path known to itself, the location of the more mature wildebeests in the crowd, and the direction of wildebeests with high mobility. The WHO algorithm imitates these traits, and can concurrently explore and exploit the search space. For validating WHO, it is applied to optimization problems and data mining tasks. It is demonstrated that WHO outperforms other evolutionary algorithms, such as genetic algorithm (GA) and particle swarm optimization, in the assessed problems. Then, WHO is applied to the customer segmentation problem. Customer segmentation is one of the most important tasks of data mining, especially in the banking sector. In this paper, the customers of a bank with current accounts are segmented using WHO based on four aspects: profitability, cost, loyalty and credit; some of these aspects are calculated in a novel way. The results were welcome by the bank authorities.<\/jats:p>","DOI":"10.1142\/s0218001419590171","type":"journal-article","created":{"date-parts":[[2018,9,18]],"date-time":"2018-09-18T07:32:22Z","timestamp":1537255942000},"page":"1959017","source":"Crossref","is-referenced-by-count":26,"title":["WHO: A New Evolutionary Algorithm Bio-Inspired by Wildebeests with a Case Study on Bank Customer Segmentation"],"prefix":"10.1142","volume":"33","author":[{"given":"Mohammad Mahdi","family":"Motevali","sequence":"first","affiliation":[{"name":"Computer Engineering Department, Islamic Azad University, Semnan Branch, Semnan 3519744571, Iran"},{"name":"Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran Province, Tehran, Al Ahmad Street No. 7. 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