Dynamic Programming Approach for Online Freeway Flow Propagation Adjustment

2002 ◽  
Vol 1802 (1) ◽  
pp. 263-270 ◽  
Author(s):  
Xuesong Zhou ◽  
Hani S. Mahmassani
Keyword(s):  
Dynamic Programming ◽  
Control Method ◽  
Dynamic Programming Algorithm ◽  
Superior Performance ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Base Case ◽  
Solution Quality ◽  
Flow Propagation ◽  
The Impact

An optimization framework for online flow propagation adjustment in a freeway context was proposed. Instead of performing local adjustment for individual links separately, the proposed framework considers the interconnectivity of links in a traffic network. In particular, dynamic behavior in the mesoscopic simulation is approximated by the finite-difference method at a macroscopic level. The proposed model seeks to minimize the deviation between simulated density and anticipated density. By taking advantage of the serial structure of a freeway, an efficient dynamic programming algorithm has been developed and tested. The experiment results compared with analytic results as the base case showed the superior performance of dynamic programming methods over the classical proportion control method. The effect of varying update intervals was also examined. The simulation results suggest that a greedy method considering the impact of inconsistency propagation achieves the best trade-off in terms of computation effort and solution quality.

scholarly journals DYNAFOLD: A DYNAMIC PROGRAMMING APPROACH TO PROTEIN BACKBONE STRUCTURE DETERMINATION FROM MINIMAL SETS OF RESIDUAL DIPOLAR COUPLINGS

2014 ◽  
Vol 12 (01) ◽  
pp. 1450002 ◽  
Author(s):  
RISHI MUKHOPADHYAY ◽  
STEPHANIE IRAUSQUIN ◽  
CHRISTOPHER SCHMIDT ◽  
HOMAYOUN VALAFAR
Keyword(s):  
Dynamic Programming ◽  
Structure Determination ◽  
Residual Dipolar Couplings ◽  
Dynamic Programming Algorithm ◽  
Synthetic Data ◽  
Dipolar Couplings ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Protein Backbone ◽  
Minimal Sets

Residual Dipolar Couplings (RDCs) are a source of NMR data that can provide a powerful set of constraints on the orientation of inter-nuclear vectors, and are quickly becoming a larger part of the experimental toolset for molecular biologists. However, few reliable protocols exist for the determination of protein backbone structures from small sets of RDCs. DynaFold is a new dynamic programming algorithm designed specifically for this task, using minimal sets of RDCs collected in multiple alignment media. DynaFold was first tested utilizing synthetic data generated for the N – H , C α– H α, and C – N vectors of 1BRF, 1F53, 110M, and 3LAY proteins, with up to ±1 Hz error in three alignment media, and was able to produce structures with less than 1.9 Å of the original structures. DynaFold was then tested using experimental data, obtained from the Biological Magnetic Resonance Bank, for proteins PDBID:1P7E and 1D3Z using RDC data from two alignment media. This exercise yielded structures within 1.0 Å of their respective published structures in segments with high data density, and less than 1.9 Å over the entire protein. The same sets of RDC data were also used in comparisons with traditional methods for analysis of RDCs, which failed to match the accuracy of DynaFold's approach to structure determination.

scholarly journals Dynamic Programming Algorithms for Computing Optimal Knockout Tournaments

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2480
Author(s):  
Amelia Bădică ◽  
Costin Bădică ◽  
Ion Buligiu ◽  
Liviu Ion Ciora ◽  
Doina Logofătu
Keyword(s):  
Dynamic Programming ◽  
Complexity Analysis ◽  
Dynamic Programming Algorithm ◽  
Experimental Results ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Optimal Algorithms ◽  
Running Time ◽  
Dynamic Programming Approach ◽  
Programming Algorithms

We study competitions structured as hierarchically shaped single-elimination tournaments. We define optimal tournaments by maximizing attractiveness such that the topmost players will have the chance to meet in higher stages of the tournament. We propose a dynamic programming algorithm for computing optimal tournaments and we provide its sound complexity analysis. Based on the idea of the dynamic programming approach, we also develop more efficient deterministic and stochastic sub-optimal algorithms. We present experimental results obtained with the Python implementation of all the proposed algorithms regarding the optimality of solutions and the efficiency of the running time.

RANKING VALID TOPOLOGIES OF THE SECONDARY STRUCTURE ELEMENTS USING A CONSTRAINT GRAPH

2011 ◽  
Vol 09 (03) ◽  
pp. 415-430 ◽  
Author(s):  
KAMAL AL NASR ◽  
DESH RANJAN ◽  
MOHAMMAD ZUBAIR ◽  
JING HE
Keyword(s):  
Dynamic Programming ◽  
Secondary Structure ◽  
Protein Complexes ◽  
Dynamic Programming Algorithm ◽  
Weighted Graph ◽  
Minimum Cost ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Constraint Graph ◽  
Density Maps

Electron cryo-microscopy is a fast advancing biophysical technique to derive three-dimensional structures of large protein complexes. Using this technique, many density maps have been generated at intermediate resolution such as 6–10 Å resolution. Although it is challenging to derive the backbone of the protein directly from such density maps, secondary structure elements such as helices and β-sheets can be computationally detected. Our work in this paper provides an approach to enumerate the top-ranked possible topologies instead of enumerating the entire population of the topologies. This approach is particularly practical for large proteins. We developed a directed weighted graph, the topology graph, to represent the secondary structure assignment problem. We prove that the problem of finding the valid topology with the minimum cost is NP hard. We developed an O(N2 2N) dynamic programming algorithm to identify the topology with the minimum cost. The test of 15 proteins suggests that our dynamic programming approach is feasible to work with proteins of much larger size than we could before. The largest protein in the test contains 18 helical sticks detected from the density map out of 33 helices in the protein.

Control and HIL Simulation of Series Hybrid Electric Vehicles Based on Dynamic Programming Algorithm

2014 ◽  
Vol 602-605 ◽  
pp. 1149-1152
Author(s):  
Liang Zhang ◽  
Bin Jiao ◽  
Xiu Hong Guo
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicles ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Control Method ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Exhaust Gas Emission ◽  
Hybrid Electric ◽  
Hil Simulation

Hybrid electric vehicles has the potential to save energy consumption and relieve exhaust gas emission while the power flow control techniques are very important for improving a hybrid electric vehicle’s performance. In this paper, the system simulation and control method of series hybrid electric vehicles were proposed. The control method was based on enhancing the energy transfer efficiency based on dynamic programming algorithm. The hardware in the loop (HIL) simulation was constructed containing a real-time driver and controller in the simulation platform, which can be used to evaluate the proposed strategy.

scholarly journals The dynamic programming approach to long term production planning in agriculture

2011 ◽  
Vol 59 (2) ◽  
pp. 129-136 ◽  
Author(s):  
Jitka Janová
Keyword(s):  
Dynamic Programming ◽  
Production Planning ◽  
Programming Model ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Goal Function ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Model Case ◽  
Local Character

The production planning in agriculture is one of the most important decision problems of the farmer. Although some decision support tools based mainly on linear programming and addressed to agriculture authorities were presented, their direct application by a farmer is not possible. This is mainly due to the local character of the models developed for particular agricultural conditions and also due to the complexness of underlying mathematical programming models.This paper aims to develop dynamic programming model for the long run crop plan optimization covering the typical conditions of Czech farms, which could serve as a platform for further enlargements and changes according to needs and conditions of particular farm. The dynamic programming algorithm is developed in detail for model case of four areas to be planted by four crops each year. The possibility of covering different constraints by generating the state space is discussed, and the generating procedure for crop rotation rules is shown. The goal function reflects the farmers objective of profit maximization and it is defined with respect to harvests’ randomness. The case study is solved for the data from South Moravian agriculture cooperative and the optimal solution is presented and discussed.

scholarly journals Are all global alignment algorithms and implementations correct?

2015 ◽  
Author(s):  
Tomáš Flouri ◽  
Kassian Kobert ◽  
Torbjørn Rognes ◽  
Alexandros Stamatakis
Keyword(s):  
Dynamic Programming ◽  
Phylogenetic Analyses ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Global Alignment ◽  
Sequence Alignments ◽  
Optimal Sequence ◽  
Divergence Time Estimates ◽  
Alignment Algorithms ◽  
The Impact

While implementing the algorithm, we discovered two mathematical mistakes in Gotoh's paper that induce sub-optimal sequence alignments. First, there are minor indexing mistakes in the dynamic programming algorithm which become apparent immediately when implementing the procedure. Hence, we report on these for the sake of completeness. Second, there is a more profound problem with the dynamic programming matrix initialization. This initialization issue can easily be missed and find its way into actual implementations. This error is also present in standard text books. Namely, the widely used books by Gusfield and Waterman. To obtain an initial estimate of the extent to which this error has been propagated, we scrutinized freely available undergraduate lecture slides. We found that 8 out of 31 lecture slides contained the mistake, while 16 out of 31 simply omit parts of the initialization, thus giving an incomplete description of the algorithm. Finally, by inspecting ten source codes and running respective tests, we found that five implementations were incorrect. Note that, not all bugs we identified are due to the mistake in Gotoh's paper. Three implementations rely on additional constraints that limit generality. Thus, only two out of ten yield correct results. We show that the error introduced by Gotoh is straightforward to resolve and provide a correct open-source reference implementation. We do believe though, that raising the awareness about these errors is critical, since the impact of incorrect pairwise sequence alignments that typically represent one of the very first stages in any bioinformatics data analysis pipeline can have a detrimental impact on downstream analyses such as multiple sequence alignment, orthology assignment, phylogenetic analyses, divergence time estimates, etc.

scholarly journals A Polynomial-Time Dynamic Programming Algorithm for Phrase-Based Decoding with a Fixed Distortion Limit

2017 ◽  
Vol 5 ◽  
pp. 59-71
Author(s):  
Yin-Wen Chang ◽  
Michael Collins
Keyword(s):  
Dynamic Programming ◽  
Dynamic Programming Algorithm ◽  
Sentence Length ◽  
Target Language ◽  
Programming Algorithm ◽  
Time Dynamic ◽  
Np Complete ◽  
New Perspective ◽  
The Traveling Salesman Problem ◽  
The Impact

Decoding of phrase-based translation models in the general case is known to be NP-complete, by a reduction from the traveling salesman problem (Knight, 1999). In practice, phrase-based systems often impose a hard distortion limit that limits the movement of phrases during translation. However, the impact on complexity after imposing such a constraint is not well studied. In this paper, we describe a dynamic programming algorithm for phrase-based decoding with a fixed distortion limit. The runtime of the algorithm is O( nd! lh d+1) where n is the sentence length, d is the distortion limit, l is a bound on the number of phrases starting at any position in the sentence, and h is related to the maximum number of target language translations for any source word. The algorithm makes use of a novel representation that gives a new perspective on decoding of phrase-based models.

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