A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Trav...
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A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). To meet these requirements, a Backtrack and Restart Genetic Algorithm (Br-GA) is proposed and compared with conventional ones, especially such as an Inner Random Restart Genetic Algorithm (Irr-GA). This method combines Backtracking and GA having simple heuristics such as 2-opt and NI (Nearest Insertion) so that, in case of stagflation, GA can restarts with the state of populations going back to the state in the generation before stagflation. Including these heuristics, field experts and field engineers can easily understand the way and use it. Using the tool applying their method, they can easily create/modify the solutions or conditions interactively depending on their field needs. Experimental results proved that the method meets the above-mentioned delivery scheduling requirements more than other methods from the viewpoint of optimality as well as simplicity. Especially as to optimality, Br-GA is superior to even Irr-GA.
A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (maximum 2 thousands or so) ...
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A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (maximum 2 thousands or so) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). To meet these requirements, an Inner Random Restart Genetic Algorithm (Irr-GA) method is proposed. This method combines random restart and GA that has different types of simple heuristics such as 2-opt and NI (Nearest Insertion). Including these heuristics, field experts and field engineers can easily understand the way and use it. Using the tool applying their method, they can easily create/modify the solutions or conditions interactively depending on their field needs. Experimental results proved that the method meets the above-mentioned delivery scheduling requirements more than other methods from the viewpoint of optimality as well as simplicity.
The accuracy and efficiency of cost estimation methodology for web-based application is very important for software development as it would be able to assist the management team to estimate the cost. Furthermore, it w...
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The accuracy and efficiency of cost estimation methodology for web-based application is very important for software development as it would be able to assist the management team to estimate the cost. Furthermore, it will ensure that the development of cost is within the planned budget and provides a fundamental motivation towards the development of web-based application project. The literature review reveals that COCOMO II provides accurate result because more variables are considered including reuse parameter. The parameter is one of the essential variables in estimating the cost in web-based application development. This research investigates the feasibility to combine and implement COCOMO II and expert judgment technique in a tool called WebCost. In estimating a cost, the tool considers all variables in COCOMO II and requires expert judgment to key-in the input of the variables such as project size, project type, cost adjustment factor and cost driven factor. Developed in JAVA, WebCost is proven able to estimate cost and generate its estimation result. The usability evaluation conducted had shown that WebCost is usable when compared with other tools, it has its own advantages. WebCost is evidence suitable for everyone especially the project managers, software practitioners or softwareengineering student in handling the cost estimation tasks.
Partly Proportionate fair (Partly-Pfair) scheduling, which allows task migration at runtime and assigns each task processing time with regard to its weight, makes it possible to build highly efficient embedded multi-c...
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Partly Proportionate fair (Partly-Pfair) scheduling, which allows task migration at runtime and assigns each task processing time with regard to its weight, makes it possible to build highly efficient embedded multi-core systems. Due to its non-work-conserving behavior, which might leave the CPU idle even when tasks are ready to execute, tasks finish only shortly before their deadlines are reached. Benefits are lower task jitter, but additional workload, e.g. through interrupts, can lead to deadline violations. In this paper we present a work-conserving extension of Partly-Pfair scheduling, called PERfair scheduling and the algorithm P-ERfair-PD2 which applies Pfair modifications used for Partly-Pfair on the concept of ERfairness and PD2 policies. With a simulation based schedulability examination we show for multiple time base (MTB) task sets that P-ERfair- PD2 has the same performance as Partly-Pfair-PD2. Additionally, we show that P-ERfair- PD2 has a much higher robustness against perturbations, and therefore it is well suited for embedded domains, especially for the Automotive domain.
In this paper, we propose a computational approach for adaptation in mission planning, an important process in the chain of command and control. In this area, it has been highly regarded that military missions are oft...
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In this paper, we propose a computational approach for adaptation in mission planning, an important process in the chain of command and control. In this area, it has been highly regarded that military missions are often dynamic and uncertain. This characteristic comes from the nature of battlefields where the factors of enemies and terrains are not easy to be determined. Hence, it is necessary to generate plans that can adapt quickly to the changes during the missions, while avoiding paying a high cost. In addressing such an adaptation process, the issue of multi-objectivity can not be avoided. Our approach first mathematically models the dynamic planning problem with two criteria: the mission execution time and the cost of operations. Based on this quantification, we introduce an evolutionary multi-objective mechanism to adapt the current solution to new situations resulted from changes. We carried out a case study on this newly proposed approach. A modified military scenario of a mission was used for testing. The obtained results strongly support our proposal in finding adaptive solution dealing with the changes.
Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising mo...
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Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising models for the physical realization of quantum computers. Despite considerable progress in the past decade, it remains a great challenge to search for new universal resource states with naturally occurring Hamiltonians and to better understand the entanglement structure of these kinds of states. Here we show that most of the resource states currently known can be reduced to the cluster state, the first known universal resource state, via adaptive local measurements at a constant cost. This new quantum state reduction scheme provides simpler proofs of universality of resource states and opens up plenty of space to the search of new resource states.
Color and geometry inconsistency between different views is an urgent problem in multi-view imaging *** this paper,we present a color correction and geometric calibration method for multi-view images on the basis of f...
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Color and geometry inconsistency between different views is an urgent problem in multi-view imaging *** this paper,we present a color correction and geometric calibration method for multi-view images on the basis of feature correspondences between ***,keypoints in views are detected by using scale invariant feature transform,and accurately matched by bi-directional feature matching between difference *** multiplicative and additive errors between matching keypoints are calculated to achieve color *** addition,an affine transformation between minimum cost matching keypoints is established to achieve geometric *** experimental results verify the effectiveness of the proposed method in color correction and geometric calibration,and a higher coding efficiency is obtained.
With the development of Grid technology and the extension of Grid application areas, it needs to provide core infrastructure platform and the necessary functional components for large-scale resources sharing and colla...
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With the development of Grid technology and the extension of Grid application areas, it needs to provide core infrastructure platform and the necessary functional components for large-scale resources sharing and collaboration. Based on the previous implementation of interactive Grid visualization system, this paper extends its runtime environment layer to provide Grid supports for the existing distributed simulation support platform and parallel graphics rendering system based on PC cluster, consequently realizes dynamic resource allocation and scheduling. Additionally, we present and implement a Grid-based distributed simulation and parallel rendering system which provides large-scale distributed simulation service and parallel rendering as well as high-resolution multi-screen tiled display service of massive complex scene to end users through an extended Grid portal.
This paper studied the calibration method for a type of embedded smart sensors which are integrated with inertial, magnetic and vision sensors. A set of calibration and modeling methods which are suitable for the low ...
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ISBN:
(纸本)9787894631046
This paper studied the calibration method for a type of embedded smart sensors which are integrated with inertial, magnetic and vision sensors. A set of calibration and modeling methods which are suitable for the low cost applications have been proposed. For the deterministic items and nondeterministic items, we used the method of modulus matching of the input vectors and the method of time series analysis to calibrate and modeling them respectively;for the relative rotation between the accelerometers' frame and the camera frame, we proposed a calibrating method which is based on the gravity vector and plumb line. The experimental and simulation results demonstrated the practicability and effectiveness of these methods.
This paper proposed an embedded smart sensor which is consisted of a 6 DOF (Degree Of Free) IMU (Inertial Measurement Unit), a 3-axis magnetic compass, a monocular camera and a DSP processor which is high performance ...
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ISBN:
(纸本)9787894631046
This paper proposed an embedded smart sensor which is consisted of a 6 DOF (Degree Of Free) IMU (Inertial Measurement Unit), a 3-axis magnetic compass, a monocular camera and a DSP processor which is high performance and power saved, and briefly discussed the design and construction of the system's hardware. By using this embedded smart sensor, we proposed a attitude determination method which is based on the quaternion and the epipolar geometry. The experimental results demonstrated the effectiveness of the methods.
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