This book presents new optimization approaches and methods and their application in real-world and industrial problems, and demonstrates how many of the problems arising in engineering, economics and other domains can...
ISBN:
(纸本)9783319598604
This book presents new optimization approaches and methods and their application in real-world and industrial problems, and demonstrates how many of the problems arising in engineering, economics and other domains can be formulated as optimization problems. Constituting a comprehensive collection of extended contributions from the 9th internationalworkshop on Computational optimization (WCO) held in Gdansk, Poland, September 1114, 2016, the book discusses important applications such as job scheduling, wildfire modeling, parameter settings for controlling different processes, capital budgeting, data mining, finding the location of sensors in a given network, identifying the conformation of molecules, algorithm correctness, decision support system, and computer memory management. Further, it shows how to develop algorithms for these based on new intelligent methods like evolutionary computations, ant colony optimization and constraint programming. The book is a valuable resource for researchers and practitioners alike.
This paper first analyzed the problems of existing ETL tools, and proposed an ETL service model based on metadata, and then summarizes the types of metadata and their application scope. Based on this ETL service model...
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As the field of design automation and generative design systems (GDS) evolve, more emphasis is placed on issues of design evaluation. This paper focus on the presentation of different applications of GENE ARCH, an evo...
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As the field of design automation and generative design systems (GDS) evolve, more emphasis is placed on issues of design evaluation. This paper focus on the presentation of different applications of GENE ARCH, an evolution-based GDS aimed at helping architects to achieve energy-efficient and sustainable architectural solutions. The system applies goal-oriented design, combining a genetic algorithm (GA) as the search engine, with the DOE2. 1E building energy simulation software as the evaluation module. Design evaluation is based on energy spent for heating, cooling, ventilation and artificial lighting in the building, and on sustainability issues like greenhouse gas emissions associated with the embodied energy of construction materials. The GA can work either as a standard GA or as a Pareto GA, for multicriteria search and optimization. In order to provide a broad view of the capabilities of the software, different applications are discussed: (1) standard GA: testing and validating the software;(2) standard GA: incorporation of architecture design intentions, using a building by architect Alvaro Siza;(3) Pareto GA: choice of construction materials, considering cost, building energy use, and embodied energy;(4) Pareto GA: application to Siza's building, considering thermal and lighting behavior separately;(5) standard GA:shape generation with single objective function;(6) Pareto GA: shape generation with multicriteria, evaluation;(7) Pareto GA: application to an urban and housing context. Overall conclusions from the different applications are discussed, as well as current challenges and limitations, and directions for further work. (C) 2007 Elsevier Ltd. All rights reserved.
This volume is the outcome of the eighth edition of the biennial workshop Algorithmic Foundations of Robotics (WAFR). Edited by G. Chirikjian, H. Choset, M. Morales and T. Murphey, the book offers a collection of a wi...
ISBN:
(数字)9783642003127
ISBN:
(纸本)9783642003110
This volume is the outcome of the eighth edition of the biennial workshop Algorithmic Foundations of Robotics (WAFR). Edited by G. Chirikjian, H. Choset, M. Morales and T. Murphey, the book offers a collection of a wide range of topics in advanced robotics, including networked robots, distributed systems, manipulation, planning under uncertainty, minimalism, geometric sensing, geometric computation, stochastic planning methods, and medical applications. The contents of the forty-two contributions represent a cross-section of the current state of research from one particular aspect: algorithms, and how they are inspired by classical disciplines, such as discrete and computational geometry, differential geometry, mechanics, optimization, operations research, computer science, probability and statistics, and information theory. Validation of algorithms, design concepts, or techniques is the common thread running through this focused collection. Richin topics and authoritative contributors,WAFR culminates with this unique reference on the current developments and new directions in the field of algorithmic foundations.
As the amount of information on the Web continues to expand, the way people access information has also changed. Instead of searching for information in paper books or libraries, people are now searching for relevant ...
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Image enhancement based on Beta function is a widely used method for it is able to fit multiple transformation curves, which is a significant step for image analysis. The key step for the method is to find the appropr...
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ISBN:
(纸本)9781728140681
Image enhancement based on Beta function is a widely used method for it is able to fit multiple transformation curves, which is a significant step for image analysis. The key step for the method is to find the appropriate parameters to determine the grayscale transformation function. However, it needs a lot of time to seek applicable parameters when enumeration is used and random optimizationalgorithms often have failures within a limited time and are prone to fall into the local optimum. In order to solve the problems a serial coupled mode of stochastic optimizationalgorithms is investigated in the paper. According to the model, the differential evolution algorithm and cuckoo search algorithm are tried in image enhancement through serial coupling mode and compared with the traditional optimization algorithm. The experimental results reveals that the proposed approach is feasible and the performance is more balanced, which has a good performance on the image enhancement.
In this article, approximation of sets is under consideration using convex polyhedrons in the three dimensional Euclidean space. In the problem statement, it is necessary to find such disposition of two given polyhedr...
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The Johnson algorithm is well known for computing an optimized job schedule for a sequence of 2 or 3 machines. However, only heuristic techniques may be applied for more than 3 machines. Among those, new iteratives te...
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ISBN:
(纸本)0444818146
The Johnson algorithm is well known for computing an optimized job schedule for a sequence of 2 or 3 machines. However, only heuristic techniques may be applied for more than 3 machines. Among those, new iteratives techniques like genetic algorithms (GA) have proven to be efficient. It is shown here that those techniques may even be better than the Johnson algorithm, for 2 and 3 machines case, due to the numerous equivalent solutions they give to the scheduling problem, hence permitting to take into account other optimisation factors, like the average time in queue. A comparison is also made with the multimachine flow shop CDS and NEH heuristics.
This volume contains the papers presented at the 11th international Wo- shop on Approximation algorithms for Combinatorial optimization Problems (APPROX 2008) and the 12th internationalworkshop on Randomization and C...
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ISBN:
(数字)9783540853633
ISBN:
(纸本)9783540853626
This volume contains the papers presented at the 11th international Wo- shop on Approximation algorithms for Combinatorial optimization Problems (APPROX 2008) and the 12th internationalworkshop on Randomization and Computation (RANDOM 2008), which took place concurrently at the MIT (M- sachusetts Institute of Technology) in Boston, USA, during August 25–27, 2008. APPROX focuses on algorithmic and complexity issues surrounding the development of e?cient approximate solutions to computationally di?cult problems, and was the 11th in the series after Aalborg (1998), Berkeley (1999), Saarbru ¨cken (2000), Berkeley (2001), Rome (2002), Princeton (2003), Cambridge (2004), Berkeley (2005), Barcelona (2006), and Princeton (2007). RANDOM is concerned with applications of randomness to computational and combinatorial problems, and was the 12th workshop in the series following Bologna (1997), Barcelona (1998), Berkeley (1999), Geneva (2000), Berkeley (2001), Harvard (2002), Princeton (2003), Cambridge (2004), Berkeley (2005), Barcelona (2006), and Princeton (2007). Topics of interest for APPROX and RANDOM are: design and analysis of - proximation algorithms, hardness of approximation, small space, sub-linear time, streaming, algorithms, embeddings and metric space methods, mathematical programming methods, combinatorial problems in graphs and networks, game t- ory, markets, economic applications, geometric problems, packing, covering, scheduling, approximate learning, design and analysis of randomized algorithms, randomized complexity theory, pseudorandomness and derandomization, random combinatorial structures, random walks/Markov chains, expander graphs and randomness extractors, probabilistic proof systems, random projections and - beddings, error-correcting codes,average-case analysis, property testing, com- tational learning theory, and other applications of approximation and randomness.
The thickness, thermal conductivity and porosity of textile material are three key factors which determine the heat-moisture comfort level of the human body to a large extent based on the heat and moisture transfer pr...
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The thickness, thermal conductivity and porosity of textile material are three key factors which determine the heat-moisture comfort level of the human body to a large extent based on the heat and moisture transfer process in the human body-clothing-environment system. This paper puts forward an Inverse Problem of Textile Thickness-Heat conductivity-Porosity Determination (IPT(THP)D) based on the steady-state model of heat and moisture transfer and the heat-moisture comfort indexes. Adopting the idea of the weighted least-squares method, we formulate IPT(THP) D into a function minimization problem. We employ the Particle Swarm optimization (PSO) method to stochastically search the optimal solution of the objective function. We put the optimal solution into the corresponding direct problem to verify the effectiveness of the proposed numerical algorithms and the validity of the IPT(THP)D.
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