Optimal Scheduling of Compressors Considering Linepack Storage in a Pipeline Network

2013 ◽  
Vol 331 ◽  
pp. 271-276
Author(s):  
Gong Tao Wang ◽  
Chen Zheng ◽  
Abed Halimah
Keyword(s):  
Dynamic Programming ◽  
Complex Systems ◽  
State Transition ◽  
Storage Capacity ◽  
Point Of View ◽  
Optimal Scheduling ◽  
Power Calculation ◽  
Pipeline Network ◽  
Multi Stage ◽  
Data Constraints

This paper presents an algorithm using dynamic programming to solve the problem of opitimal scheduling of compressors considering the linepack storage in a pipeline network. Both centrifugal and piston compressors are modelled for power calculation. For a forecast profile of gas loads, a multi-stage problem is formed by discretizing the storage capacity of linepack and tank along the timeline, and then is solved by a dynamic programming to obtain optimal day-ahead schedules for each compressor. While creating the multi-stage data, constraints on compressors, stations (sources), and pipeline network are utilized to exclude infeasible paths, avoiding dimension disaster and ensuring the feasibility of the paths from the point of view of state transition. Case studies have been done on both simple and complex systems, and the results indicate the practicability of the proposed algorithm.

Systems analysis of airport parking facilities

1978 ◽  
Vol 5 (3) ◽  
pp. 391-402
Author(s):  
Michel A. Sargious ◽  
Harvey E. Olsen
Keyword(s):  
Dynamic Programming ◽  
Systems Analysis ◽  
Systems Approach ◽  
Point Of View ◽  
Relative Importance ◽  
Planning Tool ◽  
Terminal Complex ◽  
Programming Technique ◽  
Multi Stage ◽  
Parking Facilities

In this study, a multi-stage systems approach has been discussed for implementation to planning of airport parking facilities. Six objectives were selected for comparing alternatives. Two sets of questionnaires were distributed to identify the relative importance of the objectives and the degree to which they are satisfied by the alternatives from the point of view of users and planners. A computer program, based on dynamic programming technique, was used in evaluating the alternatives and searching for the ones that are most effective in satisfying the objectives.The technique was tested, using actual data for the proposed parking facility of the new Air Terminal Complex, Calgary International Airport. The results show the applicability of the method and its usefulness as a planning tool. The actual alternative implemented at Calgary Airport, independent of this study, ranked second according to this analysis.

EFFECTIVE DYNAMIC PROGRAMMING ALGORITHMS

2020 ◽  
pp. 3-11
Author(s):  
D. A. Karpov ◽  
V. I. Struchenkov
Keyword(s):  
Dynamic Programming ◽  
Optimal Solution ◽  
Optimization Method ◽  
Point Of View ◽  
Theoretical Point ◽  
Regular Grid ◽  
Multi Stage ◽  
Effective Dynamic ◽  
Programming Algorithms ◽  
Two Parameter

This article is devoted to the analysis of the possibilities of increasing the speed of dynamic programming algorithms in solving applied problems of large dimension. Dynamic programming is considered rather than as an optimization method, but as a methodology that allows developing, from a single theoretical point of view, algorithms for solving problems that can be formalized in the form of multi-stage (multi-step) processes in which similar tasks are solved at all steps. It is shown that traditional dynamic programming algorithms based on preliminary setting of a regular grid of states are ineffective, especially if the parameters defining the states are not integer. The problems are considered, in the solution of which it is advisable to build a set of states in the process of counting, moving from one stage to another. Additional conditions are formulated that must be satisfied by the problem so that deliberately hopeless states do not fall into sets of states at each step. This ensures the rejection of not only the paths leading to each of the states, as in traditional dynamic programming algorithms, but also the unpromising states themselves, which greatly increases the efficiency of dynamic programming. Examples of applied problems are given, for the solution of which traditional dynamic programming algorithms were previously proposed, but which can be more efficiently solved by the proposed algorithm with state rejection. As applied to two-parameter problems, the concrete examples demonstrate the effectiveness of the algorithm with rejecting states in comparison with traditional algorithms, especially with increasing the dimension of the problem. An applied problem is considered, in the solution of which dynamic programming is used to construct recurrent formulas for calculating the optimal solution without enumerating options at all.

Evaluation of health system in Iraq from people's point of view: a comparative study of two different eras

2021 ◽  
Vol 4 (2) ◽  
pp. 380-387
Author(s):  
Saad Ahmed Ali Jadoo ◽  
Adil H. Alhusseiny ◽  
Shukr Mahmood Yaseen ◽  
Mustafa Ali Mustafa Al-Samarrai ◽  
Anmar Shukur Mahmood
Keyword(s):  
Health System ◽  
Health Sector ◽  
Health Resources ◽  
Sampling Technique ◽  
Point Of View ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Current Health ◽  
Multi Stage ◽  
Geographical Regions

Background: Since the 2003 United States–British Coalition military invasion, Iraq has been in a state of continuous deterioration at all levels, including the health sector. This study aimed to elicit the viewpoints of the Iraqi people on the current health system, focusing on many provided health services and assessing whether the public prefers the current health system or that was provided before the invasion. Methods: A cross-sectional survey designed to explore the Iraqi people’s opinions on their health system. A self-administered questionnaire using a multi-stage sampling technique was distributed in five geographical regions in Iraq to collect the data from the head of household between 1st October and 31st of December 2019. Multiple logistic regressions were recruited to determine the significant contributing variables in this study. Results: A total of 365 heads of households (response rate: 71.7%) with the mean age of 48.36 + 11.92 years (ranged 35-78) included in the study. Most of the respondents (61.4%) complained of healthcare inaccessibility, 59.7% believed that health resources were not available, 53.7% claimed a deterioration in the quality of care, and 62.2% believed that the political / media position did not contribute to positive changes during the past two decades. Indeed, most respondents (66.0%) believe that the current healthcare system is worse than before. In the multivariate analysis, there was a statistically significant relationship between the characteristics and opinions of the respondents. Young age group (p = 0.003), men (p = < 0.001), unmarried (p = 0.001), high educated (p = < 0.001), rural resident (p = < 0.001), unemployed (p = 0.003), monthly income of less than USD 400 (p = < 0.001), consider themselves to be unhealthy (p = 0.001),  and those who think that people are unhappy now than two decades ago (p = 0.012) have a more negative opinion of the health system. Conclusions: Most Iraqis surveyed expressed disappointment from the health system after the 2003 US-led invasion. The current health system is faltering at all levels and does not meet the citizens' basic needs. Health Transformation Program (HTP) has become inevitable to develop an accessible, affordable, high-quality, efficient, and effective health system.

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

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.

scholarly journals A dynamic alignment algorithm for imperfect speech and transcript

2010 ◽  
Vol 7 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Ye Tao ◽  
Li Xueqing ◽  
Wu Bian
Keyword(s):  
Dynamic Programming ◽  
Boundary Detection ◽  
Multimedia Content ◽  
Alignment Algorithm ◽  
Optimal Alignment ◽  
Multi Stage ◽  
Sentence Level ◽  
Sentence Boundary ◽  
English Training ◽  
Dynamic Alignment

This paper presents a novel alignment approach for imperfect speech and the corresponding transcription. The algorithm gets started with multi-stage sentence boundary detection in audio, followed by a dynamic programming based search, to find the optimal alignment and detect the mismatches at sentence level. Experiments show promising performance, compared to the traditional forced alignment approach. The proposed algorithm has already been applied in preparing multimedia content for an online English training platform.

Modularity in Artificial Neural Networks

2011 ◽  
pp. 1095-1101
Author(s):  
Ricardo Téllez ◽  
Cecilio Angulo
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Complex Systems ◽  
Intelligent Systems ◽  
Point Of View ◽  
Main Concern ◽  
Complex Structures ◽  
Computational Point ◽  
Points Of View

The concept of modularity is a main concern for the generation of artificially intelligent systems. Modularity is an ubiquitous organization principle found everywhere in natural and artificial complex systems (Callebaut, 2005). Evidences from biological and philosophical points of view (Caelli and Wen, 1999) (Fodor, 1983), indicate that modularity is a requisite for complex intelligent behaviour. Besides, from an engineering point of view, modularity seems to be the only way for the construction of complex structures. Hence, whether complex neural programs for complex agents are desired, modularity is required. This article introduces the concepts of modularity and module from a computational point of view, and how they apply to the generation of neural programs based on modules. Two levels, strategic and tactical, at which modularity can be implemented, are identified. How they work and how they can be combined for the generation of a completely modular controller for a neural network based agent is presented.

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