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AN evolutionary method OF ARRANGING THE PLOT PLAN FOR PROCESS PLANT LAYOUT

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 1991年第2期24卷 226-231页

作者： SUZUKI, A FUCHINO, T MURAKI, M HAYAKAWA, T TOKYO INST TECHNOL DEPT IND ENGN & MANAGEMENTTOKYO 152JAPAN

The equipment layout of a process plant is a multi-objective problem in which not only various costs (piping, site and so on) but also preferences about the equipment arrangement influencing its operability, maintenance and the like. It is difficult to obtain the best solution of this problem analytically. In this study, preferences are weighted as penalities so that they can be evaluated in an objective function with costs. To reduce the calculation load, equipment having spatial relations in a local area is put together into "modules" as units in layout work, and these modules are grouped into "sections" as functional groups of equipment. Furthermore, the module arrangement in each section is considered to be two variables (permutation and partition), and an algorithm based on an evolutionary method is developed to search a good plot plan efficiently. The effectiveness of this proposed method is demonstrated by an example problem.

关键词： PLANT LAYOUT evolutionary method PREFERENCE EQUIPMENT LAYOUT PLOT PLAN PLANT DESIGN

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evolutionary method for Railway Monitoring Systems 18

Evolutionary Method for Railway Monitoring Systems

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18th International Conference on System Theory, Control and Computing (ICSTCC)

作者： Daian, G., I Santa, M. M. Letia, T. S. Tech Univ Cluj Napoca Dept Automat UTCN Cluj Napoca Romania

ISBN: (纸本)9781479946013

The paper presents an evolutionary method based on genetic programming (GP) for synthesizing of a monitor alarm system for the railway control traffic unit. Automatic supervision of railway traffic control is a very important and complex task. A wrong control signal can lead to very serious incidents or accidents. A well-designed monitoring system can prevent these accidents by a simple alarm which signals the appearance of a wrong control signal. The railway network or the plant is modeled by Delay Time Petri Nets (DTPN) and the railway traffic control unit by Time Petri Nets (TPN). The alarm monitor contains transitions joined to the plant and control unit in order to achieve the information on the positions of trains, respectively the control signals of the control unit, and generates an alarm whenever the control signal can cause to an incident or accident. The TPN model of the monitor system is generated by means of the genetic programming method using a Lisp representation of the solution.

关键词： railway traffic monitoring monitoring synthesis evolutionary method safety railway traffic

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Identifying overlapping communities in networks using evolutionary method

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2016年 442卷 182-192页

作者： Zhan, Weihua Guan, Jihong Chen, Huahui Niu, Jun Jin, Guang Zhejiang Univ Dept Control Sci & Engn Hangzhou 310058 Zhejiang Peoples R China Ningbo Univ Dept Comp Sci Ningbo 315211 Zhejiang Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing 210046 Jiangsu Peoples R China Tongji Univ Coll Elect Informat & Engn Shanghai 201804 Peoples R China

Community structure is a typical property of real-world networks, and has been recognized as a key to understand the dynamics of the networked systems. In most of the networks overwhelming nodes apparently live in a community while there often exists a few nodes straddling several communities. Hence, an ideal algorithm for community detection is that which can identify the overlapping communities in these networks. We present an evolutionary method for detecting overlapping community structure in the network. To represent an overlapping division of a network, we develop an encoding scheme composed of two segments, the first one represents a disjoint partition and the second one represents an extension of the partition that allows of multiple memberships. We give two measures for the informativeness of a node, and present a coevolutionary scheme between two segments over the population for solving the overlapping partition of the network. Experimental results show this method can give a better solution to a network. It is also revealed that a best overlapping partition of the network might not be rooted from a best disjoint partition. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Community structure evolutionary method Overlapping communities

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Dynamic optimization of chemical engineering processes by an evolutionary method

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COMPUTERS & CHEMICAL ENGINEERING 1998年第7-8期22卷 1089-1097页

作者： Pham, QT Univ New S Wales Sch Chem Engn & Ind Chem Sydney NSW 2052 Australia

An evolutionary method is proposed for the constrained optimization of chemical engineering processes. Apart from the classical mutation, crossover and creep (small mutation), it makes use of several novel reproductive operators: shift, smoothing, extrapolation and swapping. An adaptive mutation rate is used to guard against stalling at local peaks. The method was able to solve dynamic optimization problems involving constrained time-dependent vectors, such as those arising in process control and inverse heat transfer. In addition, the method solves reputedly difficult test problems such as Shwefel's and Grierwangk's functions better than any known previous method. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： evolutionary method optimization dynamic optimization genetic algorithm

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A metaheuristic evolutionary method for electrical performance estimation of distribution networks

A metaheuristic evolutionary method for electrical performan...

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IEEE-Power-Engineering-Society General Meeting

作者： Hashimoto, K Kagan, N Santoso, S Sao Paulo State Energy Regulatory Commiss CSPE Sao Paulo Brazil

ISBN: (纸本)078039156X

This paper proposes a new probabilistic method to evaluate power distribution electrical performance. Electrical performance is assumed to be the evaluation of network congestion parameters, losses and voltage level. The proposed method is suitable for off-line applications and it considers steady state performance only. The electrical performance estimation is formulated as a multiobjective optimization problem where the objective functions correspond to an evaluation of occurrence probability, and also correspond to a proximity evaluation of calculated voltage levels with values obtained by measurement (goal programming). Load profile values are discretized according to its occurrence probabilities (universal discrete probability density function), so that formulation results in a multiobjective combinatorial optimization. The optimization formulation considers feeder output power and voltage level measurement in any point of the network as restriction parameters. Network reduction procedures to substantially reduce Decision Domain and network expansion procedures to rebuild it are proposed. Specific heuristics - applicable to radial networks - were also developed to generate a-priori feasible candidate solutions combining unbalanced and diversification load values. A metaheuristic evolutionary method is proposed and applied in order to improve feasible solutions and adequately apply the heuristics. Feasible solutions are classified according to Dominance Ranking algorithm, so that electrical performance is obtained for each dominance rank frontier.

关键词： electrical performance estimation. multiobjective combinatorial optimization evolutionary method metatieuristics

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PID-Fuzzy Controllers with Dynamic Structure and evolutionary method for Their Construction 38th

PID-Fuzzy Controllers with Dynamic Structure and Evolutionar...

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38th International Conference on Information Systems Architecture and Technology (ISAT)

作者： Lapa, Krystian Cpalka, Krzysztof Czestochowa Tech Univ Inst Computat Intelligence Czestochowa Poland

ISBN: (纸本)9783319672205;9783319672199

The controllers are interesting type of information systems. Their structure and parameters for atypical applications usually are selected by trial and error method, which can be time-consuming. In this paper a controller structure, which is an ensemble of PID controller and fuzzy system, and an automatic evolutionary method for its construction is presented. The significant feature of proposed method is that the controller elements, that increase its complexity but do not improve the controller precision in the sense of the adopted evaluation function, can be reduced. Moreover, this method allows to use the knowledge of the controlled object. A typical control problem has been used to test the authors approach.

关键词： evolutionary method Controller PID FIR Fuzzy system

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Acquisition of Multiple Block Preserving Outerplanar Graph Patterns by an evolutionary method for Graph Pattern Sets 10

Acquisition of Multiple Block Preserving Outerplanar Graph P...

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10th IEEE International Workshop on Computational Intelligence and Applications (IWCIA)

作者： Tokuhara, Fumiya Miyahara, Tetsuhiro Kuboyama, Tetsuji Suzuki, Yusuke Uchida, Tomoyuki Hiroshima City Univ Grad Sch Informat Sci Hiroshima 7313194 Japan Gakushuin Univ Comp Ctr Tokyo 1718588 Japan

ISBN: (纸本)9781538604694

Knowledge acquisition from graph structured data is an important task in machine learning and data mining. Block preserving outerplanar graph patterns are graph structured patterns having structured variables and are suited to represent characteristic graph structures of graph data modeled as outerplanar graphs. We propose a learning method for acquiring characteristic multiple block preserving outerplanar graph patterns by evolutionary computation using graph pattern sets as individuals, from positive and negative outerplanar graph data, in order to represent characteristic graph structures more precisely.

关键词： evolutionary method genetic programming outerplanar graphs sets of graph structured patterns

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Acquisition of Multiple Graph Structured Patterns by an evolutionary method using Sets of TTSP Graph Patterns as Individuals 6

Acquisition of Multiple Graph Structured Patterns by an Evol...

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6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

作者： Yamagata, Yuuki Miyahara, Tetsuhiro Suzuki, Yusuke Uchida, Tomoyuki Tokuhara, Fumiya Kuboyama, Tetsuji Hiroshima City Univ Fac Informat Sci Hiroshima 7313194 Japan Hiroshima City Univ Grad Sch Informat Sci Hiroshima 7313194 Japan Gakushuin Univ Comp Ctr Tokyo 1718588 Japan

ISBN: (纸本)9781538606216

Knowledge acquisition from graph structured data is an important task in machine learning and data milling. TTSP (Two-Terminal Series Parallel) graphs are used as data models for electric networks and scheduling. We propose a learning method for acquiring characteristic multiple graph structured patterns by evolutionary computation using sets of TTSP graph patterns as individuals, from positive and negative TTSP graph data, in order to represent sets of TTSP graphs more precisely.

关键词： evolutionary method genetic programming sets of graph structured patterns

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Solving Fixed Channel Allocation using Hybrid evolutionary method 4

Solving Fixed Channel Allocation using Hybrid Evolutionary M...

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4th International Conference on Advancements in Engineering and Technology (ICAET)

作者： Marappan, Raja Sethumadhavan, Gopalakrishnan SASTRA Univ Sch Comp Dept Comp Applicat Thanjavur India

Assigning channels to cells in wireless networks is an NP-hard problem. There are different soft computing strategies are applied to solve fixed channel allocation with the interference constraints of the mobile network. This research focuses on applying the new genetic operators with the local search and heuristic strategies to obtain the near optimal solution. This hybrid evolutionary method is implemented on some of the benchmark instances. Near optimal solution is obtained in the minimal complexity and the results are found to be better than the existing methods.

关键词： Fixed channel allocation genetic algorithm cellular networks evolutionary method

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Acquisition of Multiple Tree Structured Patterns by an evolutionary method using Sets of Tag Tree Patterns as Individuals 4

Acquisition of Multiple Tree Structured Patterns by an Evolu...

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IIAI 4th International Congress on Advanced Applied Informatics (IIAI-AAI)

作者： Tani, Shotarou Miyahara, Tetsuhiro Suzuki, Yusuke Uchida, Tomoyuki Hiroshima City Univ Grad Sch Informat Sci Hiroshima 7313194 Japan

ISBN: (纸本)9781479999583

Knowledge acquisition from tree structured data is an important task in machine learning and data mining. A tag tree pattern is a rooted tree structured pattern which has ordered children and structured variables representing arbitrary subtree structures. In order to represent tree structured data about complex phenomena, we propose a learning method for acquiring characteristic multiple tree structured patterns by evolutionary computation using sets of tag tree patterns as individuals, from positive and negative tree structured data.

关键词： evolutionary method genetic programming sets of tree structured patterns

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