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Techniques such as metaheuristics are promising than the heuristics, most especially when handling large scheduling request. However, addressing certain limitations attributed to the metaheuristic such as slow convergence speed and imbalance between its local and global search could enable it become even more promising for customers service selection. In this work, we propose a cloud customers service selection scheme called Dynamic Multi-Objective Orthogonal Taguchi-Cat (DMOOTC). In the proposed scheme, avoidance of local entrapment is achieved by not only increasing its convergence speed, but balancing between its local and global search through the incorporation of Taguchi orthogonal approach. To enable the scheme to meet customers\u2019 expectations, Pareto dominant strategy is incorporated providing better options for customers in selecting their service preferences. The implementation of our proposed scheme with that of the benchmarked schemes is carried out on CloudSim simulator tool. With two scheduling scenarios under consideration, simulation results show for the first scenario, our proposed DMOOTC scheme provides better service choices with minimum total execution time and cost (with up to 42.87%, 35.47%, 25.49% and 38.62%, 35.32%, 25.56% reduction) and achieves 21.64%, 18.97% and 13.19% improvement for the second scenario in terms of execution time compared to that of the benchmarked schemes. Similarly, statistical results based on 95% confidence interval for the whole scheduling scheme also show that our proposed scheme can be much more reliable than the benchmarked scheme. This is an indication that the proposed DMOOTC can meet customers\u2019 expectations while providing guaranteed performance of the whole cloud computing environment.<\/jats:p>","DOI":"10.1007\/s00521-020-04834-6","type":"journal-article","created":{"date-parts":[[2020,3,17]],"date-time":"2020-03-17T16:32:38Z","timestamp":1584462758000},"page":"14817-14838","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Cloud customers service selection scheme based on improved conventional cat swarm optimization"],"prefix":"10.1007","volume":"32","author":[{"given":"Danlami","family":"Gabi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdul Samad","family":"Ismail","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anazida","family":"Zainal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zalmiyah","family":"Zakaria","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ajith","family":"Abraham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nasiru Muhammed","family":"Dankolo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,3,17]]},"reference":[{"issue":"8","key":"4834_CR1","doi-asserted-by":"publisher","first-page":"e105297","DOI":"10.1371\/journal.pone.0105297","volume":"9","author":"Z Gui","year":"2016","unstructured":"Gui Z, Yang C, Xia J, Huang Q, Liu K, Li Z, Yu M et al (2016) A service brokering and recommendation mechanism for better selecting cloud services. 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