scholarly journals EcoRacer: Game-Based Optimal Electric Vehicle Design and Driver Control Using Human Players

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Yi Ren ◽  
Alparslan Emrah Bayrak ◽  
Panos Y. Papalambros
Keyword(s):  
Optimization Problem ◽  
Solution Space ◽  
Efficient Global Optimization ◽  
Vehicle Design ◽  
Control Problems ◽  
Short Term ◽  
Algorithm Efficiency ◽  
Np Complete ◽  
And Control

We compare the performance of human players against that of the efficient global optimization (EGO) algorithm for an NP-complete powertrain design and control problem. Specifically, we cast this optimization problem as an online competition and received 2391 game plays by 124 anonymous players during the first month from launch. We found that while only a small portion of human players can outperform the algorithm in the long term, players tend to formulate good heuristics early on that can be used to constrain the solution space. Such constraining of the search enhances algorithm efficiency, even for different game settings. These findings indicate that human-assisted computational searches are promising in solving comprehensible yet computationally hard optimal design and control problems, when human players can outperform the algorithm in a short term.

ecoRacer: Game-Based Optimal Electric Vehicle Design and Driver Control Using Human Players

2015 ◽  
Author(s):  
Yi Ren ◽  
Alparslan Emrah Bayrak ◽  
Panos Y. Papalambros
Keyword(s):  
Optimization Problem ◽  
Solution Space ◽  
Human Computation ◽  
Efficient Global Optimization ◽  
Vehicle Design ◽  
Control Problems ◽  
Np Complete ◽  
The Cost ◽  
And Control

We investigate the cost and benefit of crowdsourcing solutions to an NP-complete powertrain design and control problem. Specifically, we cast this optimization problem as an online competition, and received 2391 game plays by 124 anonymous players during the first week from the launch. We compare the performance of human players against that of the Efficient Global Optimization (EGO) algorithm. We show that while only a small portion of human players can outperform the algorithm in long term, players tend to formulate good heuristics early on, from where good solutions can be extracted and used to constrain the solution space. Incorporating this constraint into the search enhances the efficiency of the algorithm, even for problem settings different from the game. These findings indicate that human computation is promising in solving comprehensible and computationally hard optimal design and control problems.

scholarly journals A Discrete Imperialist Competitive Algorithm for WSN Deployment

2018 ◽  
Vol 7 (4.1) ◽  
pp. 4
Author(s):  
Kamal Jadidy Aval ◽  
Masumeh Damrudi
Keyword(s):  
Event Detection ◽  
Optimization Problem ◽  
Solution Space ◽  
Imperialist Competitive Algorithm ◽  
Message Delivery ◽  
Exact Methods ◽  
Network Nodes ◽  
Competitive Algorithm ◽  
Minimum Probability ◽  
Np Complete

The WSN deployment problem is addressed in this paper. The problem applies to the monitored areas with different detection needs at different points. In this problem, every point of the terrain is assigned with a predefined minimum probability of event detection. The objective is providing the best position for the network nodes and at the same time assuring event detection, detection message delivery, and reducing deployment cost. We have formulated the problem as an optimization problem with three objectives, which is NP-complete. Because of the huge solution space for the problem and the exponential computational complexity, none of the exact methods known yet can solve the problem unless for a pretty small scaled case. To battle the complexity of the solution, a new scalable solution is proposed based on imperialist competitive algorithm namely imperialist competitive deployment algorithm (ICDA). We compare the proposal to the related deployment strategies, and the results show that ICDA outperforms them.  

scholarly journals Illegal markets, human trade and transnational organised crime

Temida ◽  
2003 ◽  
Vol 6 (4) ◽  
pp. 3-13 ◽  
Author(s):  
Vesna Nikolic-Ristanovic
Keyword(s):  
Human Trafficking ◽  
Organised Crime ◽  
Social Contexts ◽  
Short Term ◽  
Illegal Markets ◽  
The Balkans ◽  
Effective Strategies ◽  
Human Trade ◽  
And Control

In this paper the author explores, focusing largely on the example of the Balkans, the connection between the expansion of neoliberal market economy and war, and related to it the growth of illegal markets and the shadow economy, on one hand, and the victimisation by human trafficking, on the other. By locating human trade within expanding local and global illegal markets, the author is arguing that, without taking into consideration wider social contexts, which create structural incentives for illegal markets and transnational organised crime, we can hardly understand the causes, let alone build effective strategies to combat and prevent it. Consequently, on the basis of the analyses of human trade as a form of both transnational organised crime and illegal markets, some strategies (short-term and long-term) for the prevention and control of human trafficking on both the micro and macro level are suggested.

Control Strategy of Soluble Boron-Free Operation for a Small PWR

2017 ◽  
Author(s):  
Guangwen Bi ◽  
Chuntao Tang ◽  
Bo Yang
Keyword(s):  
Control Strategy ◽  
Power Distribution ◽  
Short Term ◽  
Control Rod ◽  
Burnable Poison ◽  
Power Operation ◽  
And Control ◽  
Power Distribution Control ◽  
Selection Of

Elimination of soluble boron will be a challenge to reactor operation for PWR. This paper is to promote a control strategy of soluble boron-free operation for a small PWR, through selection of burnable poison (BP), BP loading and control rod loading, based on the reactivity balance and manage requirement. The analysis for on-power operation and shutdown condition indicated that this strategy could be suitable for long-term and short-term reactivity and power distribution control for soluble boron-free operation.

The Need for Strategic Planning for Nuclear Power Plant I&C Upgrades

2002 ◽  
Author(s):  
J. Douglas Hill ◽  
Paul Moore
Keyword(s):  
Strategic Planning ◽  
Control Systems ◽  
Digital Technology ◽  
Nuclear Power ◽  
Power Plants ◽  
Short Term ◽  
Nuclear Plants ◽  
And Control ◽  
Plant Control

Nuclear power plants rely on Instrumentation and Control (I&C) systems for control, monitoring and protection of the plant. The original, analog designs used in most nuclear plants have become or soon will be obsolete, forcing plants to turn to digital technology. Many factors affect the design of replacement equipment, including long-term and short-term economics, regulatory issues, and the way the plant operates on a day-to-day basis. The first step to all modernization projects should involve strategic planning, to ensure that the overall long and short-term goals of the plant are met. Strategic planning starts with a thorough evaluation of the existing plant control systems, the available options, and the benefits and consequences of these options.

The Shift towards Smart, Green and Integrated Raw Materials Efficiency

2014 ◽  
Vol 718 ◽  
pp. 105-109
Author(s):  
Eva Oravcová ◽  
Miroslav Zelko
Keyword(s):  
Decision Support ◽  
Raw Materials ◽  
Decision Makers ◽  
Short Term ◽  
Supervision System ◽  
Requirements Development ◽  
And Control ◽  
Term Data

Comprehensive environmental observation, eco-innovation and smartization are essential to ensure the delivery of the long-term data and information required to address the shift towards smart, green and integrated raw materials efficiency. For this reason we need the mine-wide digitalization and informatization base model, an advanced mine-wide decision support system and a smart supervision system to supervise and control the production, back to predefined short-term production targets with most likelihood and optimal approaches. There are three main steps to be taken: analysis, evaluation and determination of the shift requirements, development of the models as well as modeling of the scenarios and connection to the smart platform for the support of the decision makers. The paper aims to consider what would be required for a raw materials area to operate as a modern smart technology-supported business. It attempts to provide a vision of some future smart architectures scenarios.

The Development of a Generic Qualified Digital Platform

2010 ◽  
Author(s):  
Victor S. S. Shyu ◽  
Ming-Huei Chen
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Systems Design ◽  
Nuclear Industry ◽  
Regulatory Body ◽  
Short Term ◽  
Digital Platform ◽  
And Control ◽  
Nuclear Instrumentation

The nuclear industry and research institutes in Taiwan are conducting a joint effort project to establish a self-reliant nuclear Instrumentation and Control (I&C) system design and fabrication capabilities in Taiwan. The purposes of this project, as called Taiwan’s Nuclear I&C System (TaiNICS), are planned to support digital upgrade of the existing nuclear power plants and the new nuclear installations in Taiwan. The project will be a long term pursuit of several task branches, including establishment of a generic qualified digital platform, qualification and certification processes, nuclear I&C systems design, safety analyses for software common cause failure, licensing, and collaboration. The short term goal of this project is to submit the License Topical Report (LTR) of a generic digital platform for the review of Taiwan’s regulatory body in 2013.

Carbohydrate Metabolism in Fed and Fasted Rats Exposed to an Altitude of 12,470 Feet

1958 ◽  
Vol 193 (2) ◽  
pp. 415-424 ◽  
Author(s):  
Paola S. Timiras ◽  
Robert Hill ◽  
Alvin A. Krum ◽  
Adam W. Lis
Keyword(s):  
Sea Level ◽  
Heart Muscle ◽  
Glycogen Content ◽  
Level Control ◽  
Short Term ◽  
Filial Generation ◽  
Sugar Levels ◽  
And Control ◽  
Fasted Rats

Blood sugar levels and the glycogen content of liver, heart, skeletal muscle, diaphragm and kidney of both fed and fasted sea level control rats were compared with those of fed and fasted rats (P) born at sea level and then exposed to an altitude of 12,470 feet for various periods of time, and with those of fed rats (F2) of the second filial generation born and maintained at altitude. In the P animals after short-term (24 and 72 hr.) exposure, liver, heart, muscle and diaphragm glycogen was markedly decreased in the fed animals as compared with the fed sea level controls, and markedly increased in the fasted hypoxic animals as compared with the fasted sea level controls. In fed P animals after long-term exposure, liver, heart, muscle and diaphragm glycogen was the same as in fed controls after 2 and 6 months at altitude, and became markedly lower than in the controls after 10 months. In the F2 rats, liver and muscle glycogen was markedly decreased when compared with the controls; in contrast, cardiac glycogen content was significantly higher in these F2 rats than in the controls. Changes were not observed in kidney glycogen. Hyperglycemia was observed in all P rats after 24 hours, and hypoglycemia after 72 hours at altitude. In the long-term experiments glycemia was the same in experimental (P and F2) and control rats.

scholarly journals A Fast Integrated Planning and Control Framework for Autonomous Driving via Imitation Learning

2018 ◽  
Author(s):  
Liting Sun ◽  
Cheng Peng ◽  
Wei Zhan ◽  
Masayoshi Tomizuka
Keyword(s):  
Nonlinear Models ◽  
Autonomous Driving ◽  
Optimization Methods ◽  
Imitation Learning ◽  
Short Term ◽  
Model Based ◽  
Planning And Control ◽  
And Control ◽  
Optimal Driving

Safety and efficiency are two key elements for planning and control in autonomous driving. Theoretically, model-based optimization methods, such as Model Predictive Control (MPC), can provide such optimal driving policies. Their computational complexity, however, grows exponentially with horizon length and number of surrounding vehicles. This makes them impractical for real-time implementation, particularly when nonlinear models are considered. To enable a fast and approximately optimal driving policy, we propose a safe imitation framework, which contains two hierarchical layers. The first layer, defined as the policy layer, is represented by a neural network that imitates a long-term expert driving policy via imitation learning. The second layer, called the execution layer, is a short-term model-based optimal controller that tracks and further fine-tunes the reference trajectories proposed by the policy layer with guaranteed short-term collision avoidance. Moreover, to reduce the distribution mismatch between the training set and the real world, Dataset Aggregation is utilized so that the performance of the policy layer can be improved from iteration to iteration. Several highway driving scenarios are demonstrated in simulations, and the results show that the proposed framework can achieve similar performance as sophisticated long-term optimization approaches but with significantly improved computational efficiency.

Conflict Irresolution in the South China Sea

Asian Survey ◽  
2012 ◽  
Vol 52 (6) ◽  
pp. 1019-1042 ◽  
Author(s):  
David Scott
Keyword(s):  
Conflict Resolution ◽  
South China Sea ◽  
Conflict Management ◽  
South China ◽  
The South China Sea ◽  
The South ◽  
Short Term ◽  
China Sea ◽  
And Control

Abstract In the South China Sea dispute, some Track-2 settings, along with Track-1 efforts by ASEAN and China, have facilitated some conflict “management.” But they have not brought about conflict “resolution” of the basic sovereignty and control issues. Conflict “irresolution” has ensued instead. Short-term balancing may perhaps generate long-term socialization convergence.

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