This study considers joint pricing and lot-sizing policies in a single-manufacturer-single-retailer system. Because a supply chain is a hierarchical system, we adopt a bilevel programming technique to establish a bile...
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This study considers joint pricing and lot-sizing policies in a single-manufacturer-single-retailer system. Because a supply chain is a hierarchical system, we adopt a bilevel programming technique to establish a bilevel joint pricing and lot-sizing model guided by the manufacturer. The objective of the problem here is to respectively maximize the manufacturer's and the retailer's net profits by determining the manufacturer's and retailer's lot size, the wholesale price and the retail price simultaneously. Following the properties of the bilevel programming problem (BLPP), we design a novel bilevel particle swarm optimization algorithm (BPSO), and it can solve BLPP without any assumed conditions of the problem. BPSO shows a good performance on eight benchmark bilevel problems. Then BPSO is employed to solve the proposed bilevel model, and the experimental data are used to analyze the features of the proposed bilevel model, and the results support the finding that BPSO is effective in optimizing BLPP.
In this paper, we study a two-dimensional knapsack problem: packing squares as many as possible into a unit square. Our results are the following: (i) we propose an algorithm called IHS (Increasing Height Shelf), and ...
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In this paper, we study a two-dimensional knapsack problem: packing squares as many as possible into a unit square. Our results are the following: (i) we propose an algorithm called IHS (Increasing Height Shelf), and prove that the packing is optimal if in an optimal packing there are at most 5 squares, and this upper bound is sharp;(ii) if all the squares have side length at most 1/k., we propose a simple and fast algorithm with an approximation ratio k(2)-3k+2/k(2) in time O(n log n);(iii) we give an EPTAS for the problem, where the previous result in Jansen and Solis-Oba (2008)[16] is a PTAS, not an EPTAS. However our approach does not work on the previous model of Jansen and Solis-Oba (2008) [16], where each square has an arbitrary weight. (C) 2012 Elsevier B.V. All rights reserved.
Recently, many researchers in the field of automatic content-based image retrieval have devoted a remarkable amount of research looking for methods to retrieve the best relevant images to the query image. This paper p...
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Recently, many researchers in the field of automatic content-based image retrieval have devoted a remarkable amount of research looking for methods to retrieve the best relevant images to the query image. This paper presents a novel algorithm for increasing the precision in content-based image retrieval based on electromagnetism optimization technique. The electromagnetism optimization is a nature-inspired technique that follows the collective attraction-repulsion mechanism by considering each image as an electrical charge. The algorithm is composed of two phases: fitness function measurement and electromagnetism optimization technique. It is implemented on a database with 8,000 images spread across 80 classes with 100 images in each class. Eight thousand queries are fired on the database, and the overall average precision is computed. Experimental results of the proposed approach have shown significant improvement in the retrieval performance in regard to precision.
A routing algorithm named Sub-Game Energy Aware Routing (SGEAR) modeled by Dynamic Game Theory is proposed in this paper to make better routing choices. SGEAR takes the residual energy of the nodes and the energy cons...
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A routing algorithm named Sub-Game Energy Aware Routing (SGEAR) modeled by Dynamic Game Theory is proposed in this paper to make better routing choices. SGEAR takes the residual energy of the nodes and the energy consumption of the path into consideration and achieves Nash Equilibrium using Backward Induction. Compared with Energy Aware Routing, SGEAR can provide stable routing choices for relaying nodes and the energy of the network can still burn evenly. Moreover, this algorithm is more suitable for being combined with sleeping scheduling scheme and thus prolongs the lifetime of Wireless Sensor Networks. Simulation results show that, combined with sleeping scheduling scheme, SGEAR has an increase of 20% in energy saving compared with Energy Aware Routing. (C) 2012 Elsevier Ltd. All rights reserved.
Multi-chip module (MCM) substrates are designed for packing two or more semiconductor chips. On these substrates, there are open faults in the wiring, which are electrical disconnections. We must therefore test the su...
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Multi-chip module (MCM) substrates are designed for packing two or more semiconductor chips. On these substrates, there are open faults in the wiring, which are electrical disconnections. We must therefore test the substrates to detect open faults, and it is essential to establish an efficient method of testing them. One type of test method uses two probes. Two probes, each touching one edge (end) of an inter-chip wiring, are used to check for the presence of faults. Testing is complete when we have confirmed that no faults exist on the MCM substrate. The objective is to minimize the time to complete testing, that is, our aim is to design efficient routes for the two probes. In this paper, we propose a novel approach of formulating the routing problem as a shortest path problem with covering constraints (SPCC) and we also propose three algorithms for the SPCC. In computational experiments, we show that our formulation and algorithms outperform the existing method. (C) 2013 Elsevier Ltd. All rights reserved.
Scale invariants of Tchebichef moments are usually achieved by a linear combination of corresponding invariants of geometric moments or via an iterative algorithm to eliminate the scale factor. According to the proper...
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Scale invariants of Tchebichef moments are usually achieved by a linear combination of corresponding invariants of geometric moments or via an iterative algorithm to eliminate the scale factor. According to the properties of Tchebichef polynomials, we propose a new approach to construct scale invariants of Tchebichef moments. An algorithm based on matrix multiplication is also provided to efficiently compute the 3D moments and invariants. Several experiments are carried out to validate the effectiveness of our descriptors and algorithm.
Due to the importance of slack time utilization for power-aware scheduling algorithms, we propose a work-demand analysis method called parareclamation algorithm (PRA) to increase slack time utilization of the existing...
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Due to the importance of slack time utilization for power-aware scheduling algorithms, we propose a work-demand analysis method called parareclamation algorithm (PRA) to increase slack time utilization of the existing real-time DVS algorithms. PRA is an online scheduling for power-aware real-time tasks under rate-monotonic (RM) policy. It can be implemented and fully compatible with preemption-aware or transition-aware scheduling algorithms without increasing their computational complexities. The key technique of the heuristics method doubles the analytical interval and turns the deferrable workload out the potential slack time. Theoretical proofs show that PRA guarantees the task deadlines in a feasible RM schedule and takes linear time and space complexities. Experimental results indicate that the proposed method combining the preemption-aware methods seamlessly reduces the energy consumption by 14% on average over their original algorithms.
A vehicle stability control approach for four-wheel independently actuated (FWIA) electric vehicles is presented. The proposed control method consists of a higher-level controller and a lower-level controller. An adap...
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A vehicle stability control approach for four-wheel independently actuated (FWIA) electric vehicles is presented. The proposed control method consists of a higher-level controller and a lower-level controller. An adaptive control-based higher-level controller is designed to yield the vehicle virtual control efforts to track the desired vehicle motions due to the possible modeling inaccuracies and parametric uncertainties. The lower-level controller considering tire force saturation is given to allocate the required control efforts to the four in-wheel motors for providing the desired tire forces. An analytic method is given to distribute the high-level control efforts, without using the numerical-optimization-based control allocation algorithms. Simulations based on a high-fidelity, CarSim, and full-vehicle model show the effectiveness of the control approach.
The Point-Based Global Illumination (PBGI) algorithm is composed of two major steps: a caching step and a multiview rasterization step. At caching time, a dense point-sampling of the scene is shaded and organized in a...
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The Point-Based Global Illumination (PBGI) algorithm is composed of two major steps: a caching step and a multiview rasterization step. At caching time, a dense point-sampling of the scene is shaded and organized in a spatial hierarchy, with internal nodes approximating the radiance of their subtrees using spherical harmonics. At rasterization time, a microbuffer is instantiated at the unprojected position of each image pixel (receiver). Then, a view-adaptive level-of-detail of the scene is extracted in the form of a tree cut and rasterized in the receiver's microbuffer, solving for visibility using a local variant of the z-buffer. Finally, the pixel color is computed by convolving its filled microbuffer with the surface BRDF. This noise-free indirect lighting method is widely used in the industry and captures several critical lighting effects, including ambient occlusion, color bleeding, (indirect) soft-shadows and environment lighting. However, we observe a large redundancy in this algorithm, both in cuts and receivers'microbuffers, which stems from their relatively low resolution. In this paper, we propose an evolution of PBGI which exploits spatial coherence to reduce these redundant computations. Starting from a similarity-based variational clustering of the receivers, we compute a single tree cut and rasterize a single microbuffer for each cluster. This per-cluster microbuffer provides a faithful approximation of the incident radiance for distant nodes and is composited over a receiver-specific microbuffer rasterizing only the closest nodes of the cluster's cut. This factorized approach is easy to integrate in any existing PBGI implementation and offers a significant rendering speed-up for a negligible and controllable approximation error.
We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offlin...
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We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approaches. An important conclusion is that our online MR algorithms can handle the settings where the target hypothesis is not fixed but drifts with the sequence of examples. We also recap and draw connections to earlier works. This paper paves a way to the design and analysis of online manifold regularization algorithms.
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