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For example, by applying the incremental approach to normal MOGA, the obtained Incremental Multiple Objective Genetic Algorithm (IMOGA) outperforms state-of-the-art MOGAs, including Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Strength Pareto Evolutionary Algorithm (SPEA) and Pareto Archived Evolution Strategy (PAES). However, there is still an open question: how to decide the order of the objectives handled by incremental algorithms? Due to their incremental nature, it is found that the ordering of objectives would influence the performance of these algorithms. In this paper, the ordering issue is investigated based on IMOGA, resulting in a novel objective ordering approach. The experimental results on benchmark problems showed that the proposed approach can help IMOGA reach its potential best performance.<\/p>","DOI":"10.4018\/jaec.2010040101","type":"journal-article","created":{"date-parts":[[2010,4,30]],"date-time":"2010-04-30T12:16:12Z","timestamp":1272629772000},"page":"1-27","source":"Crossref","is-referenced-by-count":2,"title":["Ordered Incremental Multi-Objective Problem Solving Based on Genetic Algorithms"],"prefix":"10.4018","volume":"1","author":[{"given":"Wenting","family":"Mo","sequence":"first","affiliation":[{"name":"IBM, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng-Uei","family":"Guan","sequence":"additional","affiliation":[{"name":"Xian Jiaotong-Liverpool University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sadasivan","family":"Puthusserypady","sequence":"additional","affiliation":[{"name":"Technical University of Denmark, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jaec.2010040101-0","unstructured":"Chen, Q. 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