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The wide application of Internet technology and media technology produces more and more data which also leads the arrival of the era of big data. However, it is difficult to extract the needed information from the original data directly except some special conditions. In recent years, the development of machine learning which provide a effective way to solve this problem for us. You can obtain lower...
In this paper, an evolutionary algorithm is introduced for the NP-hard multi-criteria no-wait flow shop scheduling problems. Both makespan and total flowtime are taken into account. The proposed algorithm makes use of non-dominated sorting strategy. Corresponding objective increment properties are analyzed to improve efficiency for searching Pareto solutions. Experimental results show that the proposal...
Multi-objective flowshop scheduling problems have gained wide attention both in practical and academic fields. In this paper, a hybrid multi-objective genetic algorithm is proposed to solve multi-objective no-wait flowshop scheduling problems with both the makespan and the total flow time minimization. The proposed algorithm makes use of the principle of non-dominated sorting, coupled with the use...
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