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About 10,000 papers for “dynamic programming algorithm”

An adaptive mesh dynamic programming algorithm for robotic manipulator trajectory planning

Rebecca Richter, Andreas Britzelmeier, Matthias Gerdts · 2023

An adaptive mesh initialisation algorithm is proposed to compute a collision free trajectory of a robotic manipulator. To this end, we model the problem as a discrete optimal control problem in the joint space. Constraints are imposed on the joint positions and velocities. Moreover, nonlinear geometric collision avoidance constraints account for a detailed obstacle and robot geometry, imposing additional intricacies on the problem. The problem is solved numerically using a backward Semi-Lagrangian dynamic programming method in conjunction with a penalization of the nonconvex collision constraints, as proposed in [1]. Further, to adhere to the curse of dimensions an iterative algorithm is proposed to locally refine the initial state space discretisation. The main contribution of this paper is the introduction of a refinement criterion, which is independent of the value function and solely based on a signed distance function estimated from the collision geometry. Optimal trajectories resulting from adaptive and equidistant grid structures are compared and evaluated for the problem of a robotic manipulator operating in a dynamic environment.

Cited by 2

Maximum a posteriori probability direction finding and the dynamic programming algorithm

Yung‐Dar Huang · Journal of the Chinese Institute of Engineers · 1995

Abstract In this paper, a dynamic programming (DP) algorithm is proposed to compute the maximum a posteriori probability (MAP) estimate of the random location of multiple sources by passive sensor array. Based on the principle of optimality, the multivariate MAP decision problem can be transformed into a multistage one‐dimensional maximization problem. By a recursive computation and backward optimum searching technique, the MAP solution can be obtained. The computational complexity is much less than that of the direct MAP searching method, especially when the number of sensors and/or the number of sources is large. In addition, the DP computation technique is equally applicable both in the case of correlated sources and the case of uncorrelated sources.

Cited by 0

A sparse dynamic programming algorithm for alignment with non-overlapping inversions

Alair Pereira do Lago, Ilya Muchnik, Casimir A. Kulikowski · RAIRO - Theoretical Informatics and Applications · 2005

Alignment of sequences is widely used for biological sequence comparisons, and only biological events like mutations, insertions and deletions are considered. Other biological events like inversions are not automatically detected by the usual alignment algorithms, thus some alternative approaches have been tried in order to include inversions or other kinds of rearrangements. Despite many important results in the last decade, the complexity of the problem of alignment with inversions is still unknown. In 1992, Schniger and Waterman proposed the simplification hypothesis that the inversions do not overlap. They also presented an O(n 6 ) exact solution for the alignment with non-overlapping inversions problem and introduced a heuristic for it that brings the average case complexity down. (In this work, n is the maximal length of both sequences that are aligned.) The present paper gives two exact algorithms for the simplified problem. We give a quite simple dynamic program with O(n 4 )-time and O(n 2 )-space complexity for alignments with non-overlapping inversions and exhibit a sparse and exact implementation version of this procedure that uses much less resources for some applications with real data.

Cited by 8Open access

An improved dynamic programming algorithm for nonhomogeneous transfer line Kanban optimization

Stephane Youssef, Roland P. Malhamé · 2008

The paper is concerned with the optimization of unreliable transfer lines operated under Kanban production policies. Two cases are studied here: single-part and multi-part nonhomogeneous transfer lines. For multi-part lines, policies of ldquoparallel production of partsrdquo are considered so that methods of single-part performance analysis by decomposition could be generalized. Efficient dynamic programming based optimization algorithms are presented. Numerical results are then reported.

Cited by 0

The dynamic programming algorithm for management of real-time aircraft assignments

Yu. L. Korotkova, Yurii A. Mezentsev · Journal of Physics Conference Series · 2019

Abstract The schedule is the basis of any airline. In this paper, we provide one of the problems of schedule theory. This problem of optimal management of flight schedule is to minimize flight departure delays and to improve flight on-time performance. This paper provides a conceptual and mathematical formulation of optimizing an operating flight schedule problem. The problem solution is to manage the assignments of specific air-crafts on flights considering the operational information about the implementation of the planned flight schedule. This problem is NP-hard and can not be solved exactly for any real dimensions. We propose the parametric effective algorithm for its approximate solution and provide the statistical data for testing.

Cited by 0Open access

Question Answering Retrieval Method for Knowledge-Based with Dynamic Programming Algorithm

Liang Shouyu, Jiang Wei, Yuanwei Yang et al. · 2023

This paper provides a Chinese question and answer retrieval method based on dynamic programming algorithm. This paper aims to unify the question and answer process, which was originally divided into three sub steps, into the same process, and integrate the idea of state machine in formal language to model the entity recognition process and the question and answer retrieval process with the same model. Entity recognition is modeled as a transfer process from the initial state 0 to state 1 of the system, The question and answer retrieval process is modeled as a transition from state 1 to state 2. To ensure the accuracy and breadth of answers, and to unify the whole question and answer process from a macro perspective. In addition, this paper models the transfer process of the target entity in the question answering process as the state transfer process in the state machine, models the transit entity as the intermediate state, and models the final answer as the termination state. On this basis, the dynamic programming algorithm is used to support the overall decision making of the transition process between all states, while ensuring the operating efficiency of the system.

Cited by 0

PRODUCTION SCHEDULING OPTIMIZATION MODEL BASED ON DYNAMIC PROGRAMMING AND GENETIC ALGORITHM

XiangLong Huang, ZhengTing Li, LiKe Zhong · Journal of Computer Science and Electrical Engineering · 2025

In view of the problem that enterprises can not improve their profits due to the difficulty in planning reasonable decision-making schemes in real life, this paper proposes a dynamic programming model of production decision-making based on genetic algorithm. Firstly, a joint target benefit model considering the detection cost of parts, the purchase price of parts, semi-finished products, the assembly cost of finished products, the loss of replacement, semi-finished products, the disassembly cost of finished products, the disassembly of semi-finished products into parts, the disassembly compensation of finished products into semi-finished products, and the market price is established. Then, the genetic algorithm is used to optimize the variables of whether to detect parts, whether to detect semi-finished products, and whether to disassemble finished products ( 0-1 ). Finally, taking an actual production plan as an example, the validity of the model is verified, and the decision-making plan when the profit is the largest is obtained. This paper proposes a genetic algorithm-based dynamic programming model for production decision-making, which comprehensively considers various cost and price factors to optimize decision variables, thereby improving production efficiency and profit margins, and is verified to be valid through an actual production plan.

Cited by 0Open access

Improved dynamic programming algorithm for tracking small target of low-manoeuvring

Xiaodong Zhao, Xiangyang Liu · 2010

An update dynamic programming algorithm is presented in allusion to the features of the moving infrared small dim target. The main idea of this algorithm is that the predicting states between frames and a low threshold are applied to reduce the computation. The background noise is suppressed by the image pre-processing. The probability of detecting and false alarm are used to determine the threshold of image. Then its performance is evaluated, and some application problems are discussed. The point-trajectory sharing is used to process the candidate trajectories, which can abstract the small target accurately. Finally, the algorithm is verified feasible and performs well in the detection, recognition and track under low signal to noise ratio through simulation experiment.

Cited by 0

A Hierarchical Dynamic Programming Algorithm for Optimal Coalition\n Structure Generation

Meritxell Vinyals, Thomas C. Voice, Sarvapali D. Ramchurn et al. · arXiv (Cornell University) · 2013

We present a new Dynamic Programming (DP) formulation of the Coalition\nStructure Generation (CSG) problem based on imposing a hierarchical\norganizational structure over the agents. We show the efficiency of this\nformulation by deriving DyPE, a new optimal DP algorithm which significantly\noutperforms current DP approaches in speed and memory usage. In the classic\ncase, in which all coalitions are feasible, DyPE has half the memory\nrequirements of other DP approaches. On graph-restricted CSG, in which\nfeasibility is restricted by a (synergy) graph, DyPE has either the same or\nlower computational complexity depending on the underlying graph structure of\nthe problem. Our empirical evaluation shows that DyPE outperforms the\nstate-of-the-art DP approaches by several orders of magnitude in a large range\nof graph structures (e.g. for certain scalefree graphs DyPE reduces the memory\nrequirements by $10^6$ and solves problems that previously needed hours in\nminutes).\n

Cited by 1Open access

Performance Impact Factors for the Knapsack Algorithm Based on Dynamic Programming

David Kuhlen, Andreas Speck · 2026

The knapsack problem is a classical optimization problem in computer science that can be efficiently solved using an algorithm based on dynamic programming. This study investigates the impact of technical factors such as the number of elements, the size of the knapsack, or the sorting of elements on the performance of the algorithm. Performance refers to the speed of the algorithm implementation in solving the problem. The analysis focuses on so-called Performance Impact Factors, which are the selected influences that can affect the speed of the algorithm. While the size of the considered knapsack represents a parameterization/configuration, the number of items is directly related to the problem itself; therefore, the term Performance Impact Factors is generally used. The investigation is based on a simulation experiment. The analysis of the simulation experiment data shows that as the total number of elements and the knapsack capacity increase, the algorithm’s runtime also increases. In this context, an increase in knapsack capacity has a more pronounced negative effect on the algorithm’s runtime. An examination of sorting strategies further reveals that a prior sorting of elements by value in descending order can lead to significant deteriorations in runtime.

Cited by 0Open access

A Lattice Linear Predicate Parallel Algorithm for the Dynamic Programming Problems

Vijay K. Garg · arXiv (Cornell University) · 2022

It has been shown that the parallel Lattice Linear Predicate (LLP) algorithm solves many combinatorial optimization problems such as the shortest path problem, the stable marriage problem and the market clearing price problem. In this paper, we give the parallel LLP algorithm for many dynamic programming problems. In particular, we show that the LLP algorithm solves the longest subsequence problem, the optimal binary search tree problem, and the knapsack problem. Furthermore, the algorithm can be used to solve the constrained versions of these problems so long as the constraints are lattice linear. The parallel LLP algorithm works correctly in a distributed system setting where a processor may use an older value of a variable stored at a different processor.

Cited by 3Open access