Fan‐Chi Chang · 2008
This paper is primarily to improve the efficiency of real-time dynamic programming (RTDP) algorithm for solving Markov decision problems.Several typical convergence criteria are compared and analyzed.A criterion called optimal action criterion and a corresponding branch strategy are proposed on the basis of the upper and lower bound theory.This criterion guarantees that the agent can act earlier in a real-time decision process while an optimal policy with sufficient precision still remains.It can be proved that under certain conditions one can obtain an optimal policy with arbitrary precision by using such an incremental method.With these new techniques,a bounded incremental real-time dynamic programming (BI-RTDP) algorithm is designed.In the experiments of two typical real-time simulation systems,BI-RTDP outperforms the other state-of-the-art RTDP algorithms tested.
Cited by 2
Seung-Kil Lim, June-Young Bang, Jae-Gon Kim · RePEc: Research Papers in Economics
This study focuses on the -level batching problem with a hierarchical clustering structure. Clustering is the task of grouping a set of item types in such a way that item types in the same cluster are more similar (in some sense or another) to each other than to those in other clusters. In hierarchical clustering structure, more and more different item types are clustered together as the level of the hierarchy increases. -level batching is the process by which items with different types are grouped into several batches passed from level 1 to level sequentially for given hierarchical clustering structure such that batches in each level should satisfy the maximum and minimum batch size requirements of the level. We consider two types of processing costs of the batches: unit processing cost and batch processing cost. We formulate the -level batching problem with a hierarchical clustering structure as a nonlinear integer programming model with the objective of minimizing the total processing cost. To solve the problem optimally, we propose a multidimensional dynamic programming algorithm with an example.
Cited by 0
Franklin Djeumou Fomeni · Discrete Applied Mathematics · 2023
Cited by 7
Dayu Huang, Anke Xue, Yunfei Guo · Sensors · 2012
In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.
Cited by 15Open access
Ang, Seok Yan · DR-NTU (Nanyang Technological University) · 2009
In molecular biology, a common question often rises about a gene or protein is whether it is related to any other gene or protein. One of the most widely used approaches to distinguish if they are related is by sequence alignment. However, research has shown that sequence alignment has its limitations, where aligned sequences indicating high similarity may not share similar properties and vice versa. In this project, a structural approach is adopted to improve the sequence alignment. The structural information of the protein is analyzed, based on the alignment of proteins dihedral angles through a dynamic programming algorithm. A short introduction on the bioinformatics field was given where various biology terms and databases were explained. Past research and findings were also discussed. Structural information from PDB files was translated into dihedral angles. Alignment techniques and distance functions were then applied in the algorithm with different cost models and the resulted alignments were benchmarked. A research on some existing structural alignment algorithm was also performed. The benchmarking tool used was the Shift Error Algorithm and the results were benchmarked against one of the known existing algorithms, Dali. Although the results were not promising as Dali, there were several recommendations that could be carried out for future enhancements, such as modifying the dynamic programming cost mode and comparing subset of residues instead of single residues.
Cited by 0
BAHADIR DURAK · Figshare · 2019
Dynamic Programming Algorithm for the Static Tray Splitting Problem
Cited by 0Open access
Sixin Wang, Xiaomei Tang, Jing Li et al. · Remote Sensing · 2024
Navigation resource allocation for low-earth-orbit (LEO) constellations refers to the optimal allocation of navigational assets when the number and allocation of satellites in the LEO constellation have been determined. LEO constellations can not only transmit navigation enhancement signals but also enable space-based monitoring (SBM) for real-time assessment of GNSS signal quality. However, proximity in the frequencies of LEO navigation signals and SBM can lead to significant interference, necessitating isolated transmission and reception. This separation requires that SBM and navigation signal transmission be carried out by different satellites within the constellation, thus demanding a strategic allocation of satellite resources. Given the vast number of satellites and their rapid movement, the visibility among LEO, medium-earth-orbit (MEO), and geostationary orbit (GEO) satellites is highly dynamic, presenting substantial challenges in resource allocation due to the computational intensity involved. Therefore, this paper proposes an optimal allocation algorithm for LEO constellation navigation resources based on dynamic programming. In this algorithm, a network model for the allocation of navigation resources in LEO constellations is initially established. Under the constraints of visibility time windows and onboard transmission and reception isolation, the objective is set to minimize the number of LEO satellites used while achieving effective navigation signal transmission and SBM. The constraints of resource allocation and the mathematical expression of the optimization objective are derived. A dynamic programming approach is then employed to determine the optimal resource allocation scheme. Analytical results demonstrate that compared to Greedy and Divide-and-Conquer algorithms, this algorithm achieves the highest resource utilization rate and the lowest computational complexity, making it highly valuable for future resource allocation in LEO constellations.
Cited by 3Open access
Elena Rivas, Sean R. Eddy · arXiv (Cornell University) · 1998
We describe a dynamic programming algorithm for predicting optimal RNA\nsecondary structure, including pseudoknots. The algorithm has a worst case\ncomplexity of ${\\cal O}(N^6)$ in time and ${\\cal O}(N^4)$ in storage. The\ndescription of the algorithm is complex, which led us to adopt a useful\ngraphical representation (Feynman diagrams) borrowed from quantum field theory.\nWe present an implementation of the algorithm that generates the optimal\nminimum energy structure for a single RNA sequence, using standard RNA folding\nthermodynamic parameters augmented by a few parameters describing the\nthermodynamic stability of pseudoknots. We demonstrate the properties of the\nalgorithm by using it to predict structures for several small pseudoknotted and\nnon-pseudoknotted RNAs. Although the time and memory demands of the algorithm\nare steep, we believe this is the first algorithm to be able to fold optimal\n(minimum energy) pseudoknotted RNAs with the accepted RNA thermodynamic model.\n
Cited by 45Open access
Alair Pereira do Lago, Ilya Muchnik, Casimir Kulikowski · Springer Link (Chiba Institute of Technology) · 2005
\n \n Alignment of sequences is widely used for biological sequence\n comparisons, and only biological events like mutations, insertions\n and deletions are considered. Other biological events like\n inversions are not automatically detected by the usual alignment\n algorithms, thus some alternative approaches have been tried in order\n to include inversions or other kinds of rearrangements.\n Despite many important results in the last decade, the complexity of the\n problem of alignment with inversions is still unknown. In 1992, Schöniger\n and Waterman proposed the simplification hypothesis that the inversions do\n not overlap. They also presented an O(n6)<!-- <inline-formula content-type="tex"><alternatives><tex-math id="tex_eq1">$O(n^6)$</tex-math><inline-graphic mimetype="image" xlink:href="ita0423_tex_eq1.png" mime-subtype="png" id="img_eq1"/></alternatives></inline-formula> --> exact solution for\n the alignment with non-overlapping inversions problem and introduced a\n heuristic for it that brings the average case complexity down. (In this work, n is the maximal\n length of both sequences that are aligned.)\n The present paper gives two exact algorithms for the simplified\n problem. We give a quite simple dynamic program with O(n4)<!-- <inline-formula content-type="tex"><alternatives><tex-math id="tex_eq2">$O(n^4)$</tex-math><inline-graphic mimetype="image" xlink:href="ita0423_tex_eq2.png" mime-subtype="png" id="img_eq2"/></alternatives></inline-formula> -->-time\n and O(n2)<!-- <inline-formula content-type="tex"><alternatives><tex-math id="tex_eq3">$O(n^2)$</tex-math><inline-graphic mimetype="image" xlink:href="ita0423_tex_eq3.png" mime-subtype="png" id="img_eq3"/></alternatives></inline-formula> -->-space complexity for alignments with non-overlapping\n inversions and exhibit a sparse and exact implementation version of\n this procedure that uses much less resources for some applications\n with real data.\n\n
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Kambiz Movassaghi · 1971
While the most advanced technological means to photograph
Cited by 1Open access
In-Hun Jang, Donghoon Lee, Kwee-Bo Sim · International Journal of Fuzzy Logic and Intelligent Systems · 2005
This paper presents the target object search algorithm under Dynamic Programming (DP) in the Tree-type maze. We organized an experimental environment with the concatenation of Y-shape diverged way, small mobile robot, and a target object. By the principle of optimality, the backbone of DP, an agent recognizes that a given whole problem can be solved whether the values of the best solution of certain ancillary problem can be determined according to the principle of optimality. In experiment, we used two different control algorithms: a left-handed method and DP. Finally we verified the efficiency of DP in the practical application using our real robot.
Cited by 8Open access
Juan Zhao, Yujia Wang, Jiajia Chen et al. · 2016
Finite impulse response (FIR) digital filter is a commonly adopted signal processing unit in digital signal processing, due to its stability and easy implementation for linear phase response. To reduce the area complexity and power consumption of the filters, researchers have proposed algorithms to optimize the expression of coefficients with the reduced number of non-zero digits or power-of-two terms. This paper presents a new optimization algorithm based on elegant dynamic programming approach to minimize the number of non-zero digits in coefficient set, which yields to low logic operator cost in the filter circuit implementation. The proposed algorithm utilized the knapsack method from dynamic programming to effectively remove the redundant nonzero digits in the coefficients. Experiment results on benchmark filters show that the proposed algorithm can synthesize FIR filter coefficient with the reduced area complexity. Compared with two competing methods, the proposed algorithm can design FIR filters with an average of 14.49% to 47.73% reduced full adder cost over the competing methods.
Cited by 1
Yi Yao, Yaodong Cui · 2012
The cutting cost of general two-staged patterns is relatively high when the unit cutting cost is expensive. A dynamic programming algorithm for generating two-staged homogenous strip cutting patterns is presented in this paper. It can obviously reduce the number of cuts to maximize the pattern value. The algorithm determines the strip layout on the plate optimally at the first stage. The strips of the same homogenous block are cut jointly into pieces at the second stage. The experimental computational indicates that the algorithm is effective.
Cited by 0
Kouichi Kimura, Asako Koike, Kenta Nakai · Journal of Bioinformatics and Computational Biology · 2011
Myers' elegant and powerful bit-parallel dynamic programming algorithm for approximate string matching has a restriction that the query length should be within the word size of the computer, typically 64. We propose a modification of Myers' algorithm, in which the modification has a restriction not on the query length but on the maximum number of mismatches (substitutions, insertions, or deletions), which should be less than half of the word size. The time complexity is O(m log |Σ|), where m is the query length and |Σ| is the size of the alphabet Σ. Thus, it is particularly suited for sequences on a small alphabet such as DNA sequences. In particular, it is useful in quickly extending a large number of seed alignments against a reference genome for high-throughput short-read data produced by next-generation DNA sequencers.
Cited by 4
Christopher Smith, Semih Dinç · 2021
Image mosaicing is a challenging problem when there is one (or more) corrupt image(s) in the input sequence. Since the transformation of later images rely on the previous transformation calculations, one miscalculation error caused by the corrupt image propagates to other image transformations, which fails the whole process. It is not a trivial task to detect and remove these corrupt images, which we call “outliers”. In this paper, we propose a dynamic programming inspired outlier rejection algorithm to identify and remove the corrupt image(s) from the sequence. Our approach stores the previously calculated transformation matrices in a 2D array and determines the validity of composite transformations based on a decision criterion. This criterion identifies the transformations coming from corrupt images by comparing the direct registration of images and the composite transformations from existing matrices in the array. We have performed experiments on both synthetic and real datasets. Visual and numerical results show that the proposed algorithm is an efficient tool for detecting and rejecting the outlier image from the mosaic image.
Cited by 1
Yu Zhao, Ji Ye Yang · Advanced materials research · 2013
The time-delay delay phenomenon is a kind of widespread physical and biological phenomenon. The existence of time-delay not only give the stability of system analysis and controller design brings great difficulties but also usually make the systems unstable and even cause the system performance deteriorated. We use the adaptive dynamic iterative algorithm to solve this equation. By using the neural network to achieve the iterative algorithm, get the optimal control law of the systems with time delay. The simulation results show that the adaptive dynamic programming method to solve the optimal control of the nonlinear system is effective.
Cited by 0
Shahzad Ahmad Qureshi, Allam Tunio, Hanood Tunio et al. · 2026
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Yinglei Lai (219969) · Figshare · 2015
<p>An illustrative flow chat for the modified dynamic programming\n algorithm.</p>
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Francisco P. M. Oliveira, João Manuel R. S. Tavares · 2008
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Almaz Abdualiyev, Gulbakyt Sembina · КазУТБ · 2025
The optimal regional budget allocation problem is examined in this article, with consideration given to public opinion, strategic priorities, ROI, and long-term sustainability. A mathematical model with two tiers is suggested, with the first tier overseeing the transfer of budget across districts and the second tier managing distribution among sectors within districts. Genetic algorithms (GA) and dynamic programming (DP) are used for optimization. Data from Kazakhstan's Almaty region for the years 2022–2024 were used to evaluate the model. Five criteria - utility, inter-district discrepancy, deviation from strategic goals, stability, and computation time were used to conduct a comparative analysis. Although DP achieves the maximum total utility (up to 114.84 conventional units), it also deviates from strategic shares by up to 1.58 and has an inter-district difference of up to 1.25×10¹¹ tenge. GA, on the other hand, offers nearly perfect alignment with strategic goals (deviation of 0.03) and 2.5 times smaller disparity, although having lower utility (on average, 4–5% below DP). GA is five times faster than DP, with a constant computation time of 56 seconds. While DP is appropriate for long-term forecasting scenarios, the acquired results validate the applicability of GA in actual digital public administration situations. The created approach can be applied to participatory budgeting and decision support systems.
Cited by 0Open access