Aiming at billet stacking problem of the rolling mill, an IBF algorithm is used to assign the billet to the warehouse positions. The utilization of non-empty warehouse positions and shuffles are considered in the algo...
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ISBN:
(纸本)9783037859766
Aiming at billet stacking problem of the rolling mill, an IBF algorithm is used to assign the billet to the warehouse positions. The utilization of non-empty warehouse positions and shuffles are considered in the algorithm. Computational experiments demonstrate that the proposed algorithm is feasible and effective, competitive and able to find more high-quality solutions for problem instances than artificial method.
Spectrum sharing is a key function to provide fairness allocation as well as service satisfaction across multiple users in cognitive radio networks. Even though spectrum sharing can benefit from spectrum handoff to en...
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Spectrum sharing is a key function to provide fairness allocation as well as service satisfaction across multiple users in cognitive radio networks. Even though spectrum sharing can benefit from spectrum handoff to enhance rate performance by switching from unavailable channels to available ones, the negative impact on handoff delay can cause significant service degradation. In this work, we present a hybrid spectrum sharing strategy that includes novel static and dynamic spectrum sharing algorithms based essentially on a rate compensation approach and adapted best fit algorithms. The static scheme is applicable for some specific network configurations where spectrum handoff is not necessary. Conversely, the dynamic scheme can benefit from spectrum handoff to increase the achieved rate and also compensate for the lost rate from the unavailable periods. These two sharing schemes are operated adaptively according to the current network environment. We compare our hybrid strategy with a fully dynamic one and an optimization framework. The proposed hybrid spectrum sharing demonstrates its effectiveness in terms of improving the overall service satisfaction and reducing the number of handoffs while the achieved rate is fulfilling compared to the optimal.
Lake sediments commonly contain laminations and the occurrence and quantitative attributes of these microstrata contain signals of their depositional environment, limnological conditions, and past climate. However, th...
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Lake sediments commonly contain laminations and the occurrence and quantitative attributes of these microstrata contain signals of their depositional environment, limnological conditions, and past climate. However, the identification and measurement of laminae and their attributes remains a largely semi-manual process that is tedious, labor intensive, but subject to human error. Here, we present a method to automatically measure and accurately extract lamina properties from sediment core images. This method is comprised of four major components: (1) image enhancement that includes noise reduction and contrast enhancement to improve signal-to-background ratio and resolution of laminae;(2) identification of 1-D laminae for a user-chosen area in an image;(3) laminae connectivity analyses on the 1-D laminae to obtain a lamina stratigraphy;and (4) extraction and retrieval of the primary and derived lamination stratigraphic data. Sediment core images from Lake Hitchcock and Lake Bosumtwi were used for algorithm development and testing. Our experiments show a complete match between laminae produced by the software and manual process for images from Lake Hitchcock. Quantitative comparisons reveal an insignificant discrepancy in the number of laminae identified automatically by the software and manually by researchers, and in over 90% of the cases the position mismatch of individual laminae is less than one pixel between the software and the manual method for the experimental images from Lake Bosumtwi. (C) 2012 Elsevier Ltd. All rights reserved.
Bin packing problem(BPP) is a classical combinatorial optimization problem widely used in a wide range of fields. The main aim of this paper is to propose a new variant of whale optimization algorithm named improved L...
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Bin packing problem(BPP) is a classical combinatorial optimization problem widely used in a wide range of fields. The main aim of this paper is to propose a new variant of whale optimization algorithm named improved Levy-based whale optimization algorithm (ILWOA). The proposed ILWOA adapts it to search the combinatorial search space of BPP problems. The performance of ILWOA is evaluated through two experiments on benchmarks with varying difficulty and BPP case studies. The experimental results confirm the prosperity of the proposed algorithmin proficiency to find the optimal solution and convergence speed. Further, the obtained results are discussed and analyzed according to the problem size.
Aiming at billet stacking problem of the rolling mill, a multi-objective programming model is established. Billets on the roller are batched by clustering algorithm and then assigned to the warehouse stack positions b...
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ISBN:
(纸本)9783038350156
Aiming at billet stacking problem of the rolling mill, a multi-objective programming model is established. Billets on the roller are batched by clustering algorithm and then assigned to the warehouse stack positions by improved Clustering-based best fit algorithm (CBF). The utilization of non-empty warehouse stack positions and shuffles are considered in the algorithm. Compared to existing artificial calculation method, the proposed algorithm can not only reduce the shuffles significantly, but also improve the space utilization of warehouse stacking positions.
Efficient and timely delivery of goods in last-mile logistics is a key challenge for e-commerce companies. With the rise of drone technology, drone-based delivery has emerged as a promising solution to address the cha...
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Efficient and timely delivery of goods in last-mile logistics is a key challenge for e-commerce companies. With the rise of drone technology, drone-based delivery has emerged as a promising solution to address the challenges of traditional last-mile logistics. In light of the environmental and social challenges faced by last-mile delivery, integrating sustainability into logistics planning has become a vital requirement rather than a mere option. Drones have been identified as a potential solution to reduce greenhouse gas emissions and improve the sustainability of last-mile logistics. In this study, we present a mathematical model for the multi-depot multi-period drone delivery problem, which considers wind patterns and multi-periodicity to optimize the routing of multiple drones from multiple depots over a planning horizon of one day or shift. We included the wind profiles in our modeling to achieve a more realistic drone route planning. To address the complexity of the problem, we employ the Dantzig-Wolfe decomposition method to obtain a lower bound for the problem. Since we have a grouping problem, a novel metaheuristic algorithm, based on a grouping evolution strategy algorithm is developed for efficient drone routing. The algorithm uses the structural information along with the problem with the aid of a proposed constructive heuristic based on the well-known bestfit strategy. Results show that proposed approach, achieved a solution with a gap of 2.99% to the lower bound on average, demonstrating its effectiveness in addressing the complexity of the multi-depot multi-period drone delivery problem while considering the impact of wind patterns.
The components of container loading problems on railroad flatcar were analyzed in this paper. The constraint conditions that needed to be considered when studying this problem were determined. A loading model was esta...
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The components of container loading problems on railroad flatcar were analyzed in this paper. The constraint conditions that needed to be considered when studying this problem were determined. A loading model was established which include objective function of flatcar length utilization. The best fit algorithm was used for solving the model. The number of containers that cannot be loading with each container should be confirmed first according to railroad car loading technical constraints first, and then sort them by quantity. Finally, an example is used to implement the algorithm and the results indicated that the model and algorithm is feasible in practical application.
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