Genetic Algorithms for Applied CAD Problems

Malioukov, Sergey P.; Kureichik, Vladimir; Malioukov, Alexander S.

doi:10.1007/978-3-540-85281-0

Cited by 18 publications

(10 citation statements)

References 17 publications

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“…(грант № 16-38-00948 мол_а) Эволюционные алгоритмы в последние годы находят все более широкое приме-нение при решении практических инженерных задач [1]. Задачи выбора рацио-нальных параметров технических устройств регулярно встречаются в различ-ных областях инженерной деятельности.…”

Section: ключевые словаunclassified

Genetic Algorythm-Based Methods for Project Synthesis of Ballistic Installations with Hydrodynamic Effect

Bykov¹,

Зеленцов²

2016

HoBMSTU.SME

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Аннотация Ключевые словаПредложен метод автоматизированного поиска рациональ-ных параметров баллистических установок с гидродинами-ческим эффектом. (грант № 16-38-00948 мол_а) Эволюционные алгоритмы в последние годы находят все более широкое приме-нение при решении практических инженерных задач [1]. Задачи выбора рацио-нальных параметров технических устройств регулярно встречаются в различ-ных областях инженерной деятельности. При этом выделяют прямые и обрат-ные задачи или задачи анализа и синтеза. Под прямой задачей понимается определение характеристик устройства по заданным входным параметрам. Об-ратная задача подразумевает нахождение таких входных параметров устрой-ства, которые бы обеспечивали заданные или оптимальные в смысле выбранно-го критерия выходные характеристики. Хорошо известно, что решение задачи синтеза не единственно. В большинстве методов решения обратных задач так или иначе используют решение прямой задачи, причем, как правило, много-кратное. С учетом возможностей современных вычислительных средств слож-ность математических моделей претерпевает существенный рост и, как след-ствие, решение прямых задач становится все более ресурсоемким и затратным по времени. Таким образом, например, методы нахождения оптимальных ре-

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Section: ключевые словаunclassified

Genetic Algorythm-Based Methods for Project Synthesis of Ballistic Installations with Hydrodynamic Effect

Bykov¹,

Зеленцов²

2016

HoBMSTU.SME

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“…A., & Kureichik, V. M., 2010;Levanova, T. V., 2004), and for heuristic algorithms the achieving of the end result is not clearly predetermined, as well as the entire sequence of actions is not defined, and all the actions of the performer are not revealed. The example of heuristic search algorithms used for solving optimization problems and modeling by random selection, combination, and variation of the desired parameters using the mechanisms resembling biological evolution are genetic algorithms (Kureichik et al, 2006) The purpose of this paper is to investigate the collection of using of a probabilistic model of the algorithm at syntheses of correct algorithms. That model determines the ability to control the flexibility of the algorithm to provide structural and functional stability program implementing this algorithm, during, for example, hacker at it.…”

Section: Literature Reviewmentioning

confidence: 99%

Probabilistic Approach to the Synthesis of Algorithm for Solving Problems

Mikhaylov¹,

Bazuyeva²

2015

MAS

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This paper, based on the content of the axioms for the randomized algorithm, considers the collection of using correct algorithms at synthesis for solving the problem of probabilistic hidden Markov model. Application of this model allows forming algorithm with its flexibility according to a substantial situation for ensuring structural and functional stability of the program realizing this algorithm. We found that randomization of the algorithm, increasing its flexibility and efficiency, does not improve its risk compared with the corresponding deterministic algorithm. The synthesis of the algorithm based on hidden Markov model implies that the available observed data is used to determine hidden parameters of the most likely sequence of states, determining the synthesized algorithm. At the first strategy step, the "back and forth" algorithm is used to evaluate how well the model matches with the input data of the synthesized algorithm. At the second stage, the given hidden Markov model with the space of hidden states, initial probabilities of presence in state i and probabilities of transition from state i to state j, and basing on the observed states and using the Viterbi algorithm, the Viterbi path is found. At the third strategy stage, the hidden Markov models are corrected by optimizing the parameters of the model using the Baum-Welch algorithm.

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“…Often, time, needed to develop a VLSI device, exceed the period during which the device is in high demand. Given this, VLSI design should be implemented as soon as possible with cost minimization and consideration of devices quality [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

VLSI Placement Problem Based on Ant Colony Optimization Algorithm

Zaruba

Zaporozhets

Kureichik

2016

Advances in Intelligent Systems and Computing

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The paper discusses a modified algorithm based on the ants' behavior in nature. We suggest to apply this algorithm for solving the element placement problem-one of the most difficult problem in the VLSI design. This problem belongs to the NP-class problem that is there are no precise methods to solve this problem. Also we formulate the placement problem and choose an optimization criterion. The developed ant colony optimization (ACO) algorithm obtains optimal and quasi-optimal solutions during polynomial time. The distinguish feature of the algorithm is that alternative solution are represented as an undirected graph with weighted edges. Besides, at each generation the algorithm creates a taboo-list to eliminate the quantity of agent (ant) which is wrong from the point of view the using of Reverse Polish notation. To compare obtained results with known analogous algorithms we developed software which allows to carry out experiments on the basis of IBM benchmarks. Conducted experiments shown that the ACO algorithm is better than the other algorithms an average of 9 %.

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Genetic Algorithms for Applied CAD Problems

Cited by 18 publications

References 17 publications

Genetic Algorythm-Based Methods for Project Synthesis of Ballistic Installations with Hydrodynamic Effect

Genetic Algorythm-Based Methods for Project Synthesis of Ballistic Installations with Hydrodynamic Effect

Probabilistic Approach to the Synthesis of Algorithm for Solving Problems

VLSI Placement Problem Based on Ant Colony Optimization Algorithm

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