To solve the twin 40ft handing system for container terminal yard allocation, a rolling-horizon model of outbound container yard allocation planning is developed by the multi-objective planning method. Then a particle...
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ISBN:
(纸本)9783037852125
To solve the twin 40ft handing system for container terminal yard allocation, a rolling-horizon model of outbound container yard allocation planning is developed by the multi-objective planning method. Then a particleswarmalgorithm is designed to obtain the optimum solution of the model. Finally, a numerical experiment shows that the proposed approach can solve the problem effectively.
A novel non-planar coding metasurface optimized by discrete particle swarm algorithm (DPSO) is proposed in terms of the property of wideband radar cross-section (RCS) and diffuse scattering. The design consists of two...
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A novel non-planar coding metasurface optimized by discrete particle swarm algorithm (DPSO) is proposed in terms of the property of wideband radar cross-section (RCS) and diffuse scattering. The design consists of two unit cells, "0" and "1", which have a 180 degrees +/- 37 degrees phase difference for phase interference cancellation. The 10 dB monostatic RCS reduction frequency range of the metasurface is from 6.4 to 29.6 GHz, and its bandwidth ratio is 4.62:1, under normal incidence of the two polarizations. Compared to the planar surface, the non-planar surface has a greater bandwidth with respect to the monostatic and bistatic RCS reduction. The results declare its properties of ultra-wideband, angle insensitivity, and polarization insensitivity. Finally, the theoretical analysis, simulation, and experimental results match perfectly, indicating that the metasurface can be used in the RCS reduction or other microwave applications with wider RCS reduction and diffuse scattering.
A hybrid optimization method for the production of work order group furnaces was proposed in this paper. First, a working order group furnace model was constructed including performance index, the constraint condition...
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A hybrid optimization method for the production of work order group furnaces was proposed in this paper. First, a working order group furnace model was constructed including performance index, the constraint condition and the decision variable to fit the problems in working order group furnaces. The hybrid optimization method consists of an optimal priority and a variable neighborhood search algorithm. In the algorithm, we have adopted a lot of rules and corresponding grade limits on stock production. Based on the proposed algorithm's calculation results, the delivery time deviation, grade deviation and priority deviation of the 20 group furnace production orders are reduced from 58 to 42 with reduction rate of 27.59%. The satisfaction rate for grade preparation is increased from 4 to 6, which has a rate of increase of 50%. In order to prove the effectiveness of the proposed algorithm, the proposed algorithm is compared with other literature algorithms such as a discrete particle swarm algorithm, a variable neighborhood search algorithm and an adaptive variable neighborhood search algorithm.
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