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About 10,000 papers for “dynamic programming algorithm”

A Directional Time-Frequency Distribution Instantaneous Frequency Estimation Algorithm Based on Improved Dynamic Programming Algorithm

Yu Huang, Gang Yu · 2024

When the potential time-frequency distribution is affected by components of the signal intersecting in the time-frequency space, algorithms for estimating instantaneous frequency based on time-frequency analysis often fall short of the desired performance. This article uses a general linear chirplet transform to obtain a more concentrated time-frequency representation of energy, and introduces a modified version of the dynamic programming algorithm that leverages both the direction and amplitude of signal elements to determine the instantaneous frequency of overlapping components, effectively addressing the aforementioned issue.

Cited by 0

Comparison of Dynamic Programming Algorithm and Greedy Algorithm on Integer Knapsack Problem in Freight Transportation

Global Ilham Sampurno, Endang Sugiharti, Alamsyah Alamsyah · Scientific Journal of Informatics · 2018

At this time the delivery of goods to be familiar because the use of delivery of goods services greatly facilitate customers. PT Post Indonesia is one of the delivery of goods. On the delivery of goods, we often encounter the selection of goods which entered first into the transportation and held from the delivery. At the time of the selection, there are Knapsack problems that require optimal selection of solutions. Knapsack is a place used as a means of storing or inserting an object. The purpose of this research is to know how to get optimal solution result in solving Integer Knapsack problem on freight transportation by using Dynamic Programming Algorithm and Greedy Algorithm at PT Post Indonesia Semarang. This also knowing the results of the implementation of Greedy Algorithm with Dynamic Programming Algorithm on Integer Knapsack problems on the selection of goods transport in PT Post Indonesia Semarang by applying on the mobile application. The results of this research are made from the results obtained by the Dynamic Programming Algorithm with total weight 5022 kg in 7 days. While the calculation result obtained by Greedy Algorithm, that is total weight of delivery equal to 4496 kg in 7 days. It can be concluded that the calculation results obtained by Dynamic Programming Algorithm in 7 days has a total weight of 526 kg is greater when compared with Greedy Algorithm.

Cited by 19Open access

A FAST DYNAMIC PROGRAMMING ALGORITHM FOR STOPE BOUNDARY LAYOUT FOR UNDERGROUND MINE

Sakirudeen A. Abdulsalaam · International Journal of Advanced Research · 2021

We developed an efficient algorithm that generates optimal stope layout for an underground mine. After a mining site has been identified and an exploration has been done, the data gathered is analysed and a modelling technique is applied to produce an ore body. The ore body is divided into thousands of mining blocks in three dimensions. The blocks are assigned values per tonne. The miners desire a stope layout which maximizes the mine value. In this paper, we present a fast algorithm that generates the stope layout efficiently without violating the physical constraints.

Cited by 1Open access

A dynamic programming algorithm for generating chemical isomers based on frequency vectors

Ryota Ido, Naveed Ahmed Azam, Jianshen Zhu et al. · Scientific Reports · 2025

We propose a dynamic programming algorithm that generates chemical isomers of a given chemical compound with cycles. We represent a chemical compound as a chemical graph and define its feature vector based on graph-theoretical descriptors. Our descriptors mainly consist of the occurrence of "edge-configuration" that captures the information of adjacent atoms such as their degrees and bond-multiplicity. We call two chemical graphs chemical isomers of each other if they have the same feature vector and share a common prescribed structure. Our proposed algorithm produces a compact representation of all chemical isomers of a given chemical graph. This representation enables efficient counting of chemical isomers without requiring explicit generation. Furthermore, our algorithm allows us to enumerate any number of isomers, even at random. For example, our compact representation for a chemical graph with 70 non-hydrogen atoms contains around 400 arcs in which [Formula: see text] chemical isomers are embedded. The proposed algorithm serves as a powerful tool for accelerating chemical compound exploration, particularly in drug discovery and material science, where identifying novel molecular structures is critical. By efficient enumeration of isomers, our approach enhances the search space exploration for target chemical compounds, facilitating advancements in molecular design.

Cited by 2Open access

A versatile matching algorithm based on dynamic programming with circular order preserving

Francisco P. M. Oliveira, João Manuel R. S. Tavares, Todd C. Pataky · Open Repository of the University of Porto (University of Porto) · 2009

This paper presents an assignment algorithm with circular order preserving constraint. Given a cost affinity matrix and the desired percentage of correspondences, the algorithm implemented using dynamic programming determines the correspondence of type one-to-one of minimum global cost. Here, it was applied to optimize the global matching between two sets of ordered points that represent the contours of objects previously segmented from images. In the tests performed, we considered affinity matrices previously built based on information on curvature and distance to centroid. The results that have been obtained are better than the ones presented in previous studies, for the cases in which partial deformations or occlusions are involved.

Cited by 6Open access

DEVELOPMENT AND VALIDATION OF DYNAMIC PROGRAMMING ALGORITHM FOR ECO APPROACH AND DEPARTURE

Vasu Goyal · 2021

Eco Approach and Departure (Eco-AnD) is a Connected and Automated Vehicle (CAV) technology developed to reduce energy for crossing a signalized intersection or set of intersections in a corridor that features vehicle to infrastructure (V2I) communication capability. Eco-AnD technology uses the information of the signal phase and timings (SPaT) received from the V2I communication to optimize the vehicle’s speed profile and produce an energy-efficient maneuver to cross the intersection. The Eco-AnD algorithm is devised for two vehicles (GM-Volt Gen II & GM-Bolt), both with different powertrain architectures but capable of working in electric-only mode. In simulations, the developed algorithm showed an energy-saving potential of 70-90 kJ per intersection around the corridor of the MTU drive cycle for both vehicles. For the RSU loop (a subset of MTU drive cycle) up to 8 % of energy reduction is observed. Vehicle level testing of the optimized speed profiles was carried out at the American Center of Mobility (ACM) on GM-Volt Gen II to demonstrate an energy-saving of 40-50 kJ per intersection on real road conditions.

Cited by 1Open access

An Asymptotically Efficient Simulation-Based Algorithm for Finite Horizon Stochastic Dynamic Programming

Hyeong Soo Chang, Michael C. Fu, Jiaqiao Hu et al. · IEEE Transactions on Automatic Control · 2007

We present a simulation-based algorithm called "Simulated Annealing Multiplicative Weights" (SAMW) for solving large finite-horizon stochastic dynamic programming problems. At each iteration of the algorithm, a probability distribution over candidate policies is updated by a simple multiplicative weight rule, and with proper annealing of a control parameter, the generated sequence of distributions converges to a distribution concentrated only on the best policies. The algorithm is "asymptotically efficient," in the sense that for the goal of estimating the value of an optimal policy, a provably convergent finite-time upper bound for the sample mean is obtained

Cited by 21

Obtaining smoother singular arc policies using a modified iterative dynamic programming algorithm

Arun Tholudur, W. Fred Ramirez · International Journal of Control · 1997

Dynamic programming is a very powerful technique for the optimization of dynamic systems. With the ready availability of high-speed computers and the development of the iterative dynamic programming (IDP) algorithm, a feasible alternative to the calculus of variations approach to the optimal control problem is now available. Inherent in the IDP algorithm is the application of piecewise constant discretized controls. This often leads to singular optimal control policies that are highly active. The aim of this research is to modify the IDP algorithm to reduce the control energy variations that are typical of IDP while at the same time developing policies that are very close to the true optimal control. This is achieved by including a filter within the IDP procedure. Two types of filtering schemes are considered: a median filter and a first-order filter. Application of this modified algorithm to two bioreactor systems that yield singular optimal control profiles is presented and the usefulness of this scheme is demonstrated.

Cited by 49

A novel adaptive heuristic dynamic programming-based algorithm for aircraft confrontation games

Yi Mao, Zhijie Chen, Yi Yang et al. · Fundamental Research · 2021

Intelligent confrontation has become a vital technology for future air combats. Confrontation games between a penetrating aircraft and an intercepting aircraft are essential for modern air combats. In addition, the performance indexes of both the interceptor and penetrator must be considered. Traditional methods only solve one side's guidance problem without considering the intelligence of the opponent. In this paper, an adaptive heuristic dynamic programming-based algorithm is proposed for aircraft confrontation games. This algorithm constructs a heuristic dynamic programming model for both confrontation aircraft and then updates the critical and action network parameters using the dynamic confrontation state information. Numerical simulations indicate that the proposed algorithm can optimize the guidance law for both the interceptor and penetrator and is therefore superior to traditional proportional navigation methods.

Cited by 5Open access

A Dynamic Programming Algorithm for Finding an Optimal Sequence of Informative Measurements

Peter Loxley, Ka Wai Cheung · arXiv (Cornell University) · 2021

An informative measurement is the most efficient way to gain information about an unknown state. We present a first-principles derivation of a general-purpose dynamic programming algorithm that returns an optimal sequence of informative measurements by sequentially maximizing the entropy of possible measurement outcomes. This algorithm can be used by an autonomous agent or robot to decide where best to measure next, planning a path corresponding to an optimal sequence of informative measurements. The algorithm is applicable to states and controls that are either continuous or discrete, and agent dynamics that is either stochastic or deterministic; including Markov decision processes and Gaussian processes. Recent results from the fields of approximate dynamic programming and reinforcement learning, including on-line approximations such as rollout and Monte Carlo tree search, allow the measurement task to be solved in real time. The resulting solutions include non-myopic paths and measurement sequences that can generally outperform, sometimes substantially, commonly used greedy approaches. This is demonstrated for a global search task, where on-line planning for a sequence of local searches is found to reduce the number of measurements in the search by approximately half. A variant of the algorithm is derived for Gaussian processes for active sensing.

Cited by 0Open access

Four-head Laser Cutting Path Optimization Based on Dynamic Programming-Genetic Algorithm

Jin Lan Bai, Juan Chen · 2025

Under the background of Industry 4.0, the trend towards intelligence in the manufacturing industry is an important global industrial development trend. How to use emerging technologies and intelligent methods to achieve high efficiency and low consumption in the manufacturing industry is a major important proposition. In the context of laser processing enterprises, single-head cutting and double-head cutting are still the current mainstream cutting methods. How to improve the cutting efficiency without sacrificing the processing accuracy is the current mainstream research direction. Therefore, we will conduct research on the optimization of the laser cutting path for four heads, and decompose the problem of optimizing the laser cutting path for four heads into two sub-problems. For the sub-problem of collaborative partitioning, we propose a collaborative partitioning algorithm for laser cutting with four heads based on time balance; for the sub-problem of path optimization within the partition, we propose a 3DPGA algorithm based on the dynamic programming-genetic algorithm, and verify the practicality of the algorithm through experiments.

Cited by 0

A Lattice Linear Predicate Parallel Algorithm for the Dynamic\n Programming Problems

Vijay K. Garg · arXiv (Cornell University) · 2021

It has been shown that the parallel Lattice Linear Predicate (LLP) algorithm\nsolves many combinatorial optimization problems such as the shortest path\nproblem, the stable marriage problem and the market clearing price problem. In\nthis paper, we give the parallel LLP algorithm for many dynamic programming\nproblems. In particular, we show that the LLP algorithm solves the longest\nsubsequence problem, the optimal binary search tree problem, and the knapsack\nproblem. Furthermore, the algorithm can be used to solve the constrained\nversions of these problems so long as the constraints are lattice linear. The\nparallel LLP algorithm requires only read-write atomicity and no higher-level\natomic instructions.\n

Cited by 0Open access

Research on multi-beam survey line system based on dynamic programming algorithm

Xiaoya Chen, Xuanyu Chen · Applied and Computational Engineering · 2024

This paper establishes a calculation model for the coverage width and overlap rate of a multi-beam survey line system [1], and optimizes the multi-beam bathymetric survey plan for marine areas. Through the dynamic programming algorithm, a reasonable survey line plan is designed based on the actual marine area depth. The research content includes: Model Establishment: Construct a calculation model for coverage width and overlap rate, determining the coverage width and overlap rate at each position. Three-Dimensional Space Model: Using the survey vessel as the origin and combining marine area information, solve for the coverage width at different angles. Shortest Survey Line Plan: Using the dynamic programming algorithm, determine the shortest survey line plan, with the dynamic transfer equation determined by the overlap rate index. The total length of the survey line in this plan is calculated to be 114,824 meters. Specific Survey Line Plan Design: Using sea depth data and cubic spline interpolation to complete the discrete point plane, construct approximate width and slope. Under the condition of relaxing the overlap rate to 5%-30%, the shortest survey line length is obtained as 398,059 meters, with a missing survey area ratio of 0%, and the total length of parts with an overlap rate exceeding 20% is 25,759 meters, accounting for 6.4%. This study provides theoretical basis and calculation methods for optimizing multi-beam bathymetric survey plans.

Cited by 0Open access

A New Alternating Suboptimal Dynamic Programming Algorithm with Applications for Feature Selection

David Podgorelec, Borut Žalik, Domen Mongus et al. · Preprints.org · 2024

Feature selection is predominantly used in machine learning tasks, such as classification and regression. It selects a subset of features (relevant attributes of data points) from a larger set that contributes as optimally as possible to the informativeness of the model. There are exponentially many subsets of a given set, and thus, the exhaustive search is only practical for problems with at most a few dozen features. In the past, there have been attempts to reduce the search space using dynamic programming. However, models that consider similarity in pairs of features besides the quality of individual features do not provide the required optimal substructure. As a result, algorithms, which we will call suboptimal dynamic programming algorithms, find a solution that may deviate significantly from the optimal one. In this paper, we propose a dynamic programming algorithm with an iterative upgrade where the order of feature processing is inverted in each iteration. Such an alternating approach allows for improving the optimization function by using the score from the previous iteration to estimate the contribution of unprocessed features. The iterative process is proven to converge and terminate when the solution does not change in three successive iterations or when the number of iterations reaches the threshold. Results in more than 90 % of tests align with those of the exhaustive search, being competitive and often superior to the reference greedy approach. The validation was done by comparing the scores of output feature subsets and examining the accuracy of different classifiers learned on these features. In the context of feature selection, the proposed algorithm can be characterized as a filter method. However, we expect that the idea of alternating suboptimal optimization will soon be generalized to tasks beyond feature selection.

Cited by 1Open access

Integrated Scheduling and Control System of Microgrid Based on Dynamic Programming Algorithm

Bin Chen, Jiang Jiang, Yanning Shao · 2023

With the continuous development of the Internet, the technical requirements for microgrids are also constantly improving. Today, micropower applications are mainly found in industrial and commercial areas, urban areas and remote areas. With the rapid development of computers and telecommunication equipment, microgrids are also integrated into the fields of computers, control technology, algorithm strategies, etc., and gradually change to the direction of automation. Microgrid technology is becoming a new force in network systems to make up for the deficiencies of traditional networks. Therefore, the development of microgrid is very important to the development of power grid. This paper aims to study the integrated dispatch and control system of microgrid based on dynamic programming algorithm. On the basis of analyzing the comparison between dynamic programming algorithm and other algorithms and the requirements of the integrated system of regulation, the integrated dispatching and control system of microgrid is analyzed. In order to verify the advantages of the proposed algorithm, this paper compares the dynamic programming algorithm with the traditional algorithms GA and PSO. The results show that the dynamic programming algorithm can directly calculate the optimal value of multiple data blocks, which speeds up the convergence process, thus greatly reducing the iteration cycle of the algorithm, and can better meet the needs of automatic power generation instruction cycle.

Cited by 1