Cloud-Based Multidimensional Parallel Dynamic Programming Algorithm for a Cascade Hydropower System

Abstract An optimization technique based on the well known Dynamic Programming Algorithm is applied to the motion control trajectories and path planning of multi-jointed fingers in dextrous hand designs. A three fingered hand with each finger containing four degrees of freedom is considered for analysis. After generating the kinematics and dynamics equations of such a hand, optimum values of the joints torques and velocities are computed such that the finger-tips of the hand are moved through their prescribed trajectories with the least time or/and energy to reach the object being grasped. Finally, optimal as well as feasible solutions for the multi-jointed fingers are identified and the results are presented.

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Text Compare and Grouping Program using Dynamic Programming Algorithm

10.1109/ri2c51727.2021.9559779 ◽

2021 ◽

Author(s):

Auttanit Wongjak

Keyword(s):

Dynamic Programming ◽

Dynamic Programming Algorithm ◽

Programming Algorithm

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Optimal scheduling algorithms of system chip power density based on network on chip

Izvestiya vysshikh uchebnykh zavedenii. Fizika ◽

10.17223/00213411/64/9/120 ◽

2021 ◽

pp. 120-127

Author(s):

Jiashen Li ◽

◽

Yun Pan ◽

Keyword(s):

Dynamic Programming ◽

Power Density ◽

Simulated Annealing Algorithm ◽

Dynamic Programming Algorithm ◽

Network On Chip ◽

Thermal Design ◽

Optimal Scheduling ◽

Programming Algorithm ◽

System Throughput ◽

On Chip

The improvement of chip integration leads to the increase of power density of system chips, which leads to the overheating of system chips. When dispatching the power density of system chips, some working modules are selectively closed to avoid all modules on the chip being turned on at the same time and to solve the problem of overheating. Taking 2D grid-on-chip network as the research object, an optimal scheduling algorithm of system-on-chip power density based on network-on-chip (NoC) is proposed. Under the constraints of thermal design power (TDP) and system, dynamic programming algorithm is used to solve the optimal application set throughput allocation from bottom to top by dynamic programming for the number and frequency level of each application configuration processor under the given application set of network-on-chip. On this basis, the simulated annealing algorithm is used to complete the application mapping aiming at heat dissipation effect and communication delay. The open and closed processor layout is determined. After obtaining the layout results, the TDP is adjusted. The maximum TDP constraint is iteratively searched according to the feedback loop of the system over-hot spots, and the power density scheduling performance of the system chip is maximized under this constraint, so as to ensure the system core. At the same time, chip throughput can effectively solve the problem of chip overheating. The experimental results show that the proposed algorithm increases the system chip throughput by about 11%, improves the system throughput loss, and achieves a balance between the system chip power consumption and scheduling time.

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Lot-sizing problem with several production centers

Pesquisa Operacional ◽

10.1590/s0101-74382005000300010 ◽

2005 ◽

Vol 25 (3) ◽

pp. 479-492 ◽

Cited By ~ 1

Author(s):

Franklina Maria Bragion de Toledo ◽

André Luís Shiguemoto

Keyword(s):

Dynamic Programming ◽

Lot Sizing ◽

Dynamic Programming Algorithm ◽

Production Capacity ◽

Efficient Implementation ◽

Programming Algorithm ◽

Future Research ◽

Production Environment ◽

Lot Sizing Problem ◽

Forward Dynamic Programming

In this paper, a case study is carried out concerning the lot-sizing problem involving a single item production planning in several production centers that do not present capacity constraints. Demand can be met with backlogging or not. This problem results from simplifying practical problems, such as the material requirement planning (MRP) system and also lot-sizing problems with multiple items and limited production capacity. First we propose an efficient implementation of a forward dynamic programming algorithm for problems with one single production center. Although this does not reduce its complexity, it has shown to be rather effective, according to computational tests. Next, we studied the problem with a production environment composed of several production centers. For this problem two algorithms are implemented, the first one is an extension of the dynamic programming algorithm for one production center and the second one is an efficient implementation of the first algorithm. Their efficiency are shown by computational testing of the algorithms and proposals for future research are presented.

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