An effective discrete invasive weed optimization algorithm for lot-streaming flowshop scheduling problems |
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Authors: | Hong-Yan Sang Quan-Ke Pan Pei-Yong Duan Jun-Qing Li |
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Affiliation: | 1.School of Computer Science,Liaocheng University,Liaocheng,China;2.School of Mechatronic Engineering and Automation,Shanghai University,Shanghai,China |
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Abstract: | Lot-streaming scheduling problem has been an active area of research due to its important applications in modern industries. This paper deals with the lot-streaming flowshop problem with sequence-dependent setup times with makespan criterion. An effective discrete invasive weed optimization (DIWO) algorithm is presented with new characteristics. A job permutation representation is utilized and an adapted Nawaz–Enscore–Ham heuristic is employed to ensure an initial weed colony with a certain level of quality. A new spatial dispersal model is designed based on the normal distribution and the property of tangent function to enhance global search. A local search procedure based on the insertion neighborhood is employed to perform local exploitation. The presented DIWO is calibrated by means of the design of experiments approach. A comparative evaluation is carried out with several best performing algorithms based on a total of 280 randomly generated instances. The numerical experiments show that the presented DIWO algorithm produces significantly better results than the competing algorithms and it constitutes a new state-of-the-art solution for the lot-streaming flowshop problem with sequence-dependent setup times with makespan criterion. |
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