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Solving irregular econometric and mathematical optimization problems with a Genetic Hybrid Algorithm

Computational Economics 1999年第2期13卷 103-115页

作者： Ostermark, Ralf Department of Business Administration Åbo Akademi University ÅBO Finland e-mail

In the present paper we apply a new Genetic Hybrid Algorithm (GHA) to globally minimize a representative set of ill-conditioned econometric/mathematical functions. The genetic algorithm was specifically designed for nonconvex mixed integer nonlinear programming problems and it can be successfully applied to both global and constrained optimization. In previous studies, we have demonstrated the efficiency of the GHA in solving complicated NLP, INLP and MINLP problems. The present study is a continuation of this research, now focusing on a set of highly irregular optimization problems. In this paper we discuss the genetic hybrid algorithm, the nonlinear problems to be solved and present the results of the empirical tests.

关键词： Econometric functions evolutionary programming Nonlinear programming Optimization

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EVOLVING NEURAL NETWORKS FOR DETECTING BREAST-CANCER

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CANCER LETTERS 1995年第1期96卷 49-53页

作者： FOGEL, DB WASSON, EC BOUGHTON, EM MAUI MEM HOSP WAILUKU HI 96793 USA MAUI ECON DEV BOARD MAUI HI 96753 USA

Artificial neural networks are applied to the problem of detecting breast cancer from histologic data. evolutionary programming is used to train the networks. This stochastic optimization method reduces the chance of becoming trapped in locally optimal weight sets. Preliminary results indicate that very parsimonious neural nets can outperform other methods reported in the literature on the same data. The results are statistically significant.

关键词： BREAST CANCER NEURAL NETWORKS evolutionary programming

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Optimized overcomplete signal representation and its applications to time-frequency analysis of electrogastrogram

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ANNALS OF BIOMEDICAL ENGINEERING 1998年第5期26卷 859-869页

作者： Wang, ZS He, ZY Chen, JDZ Lynn Inst Healthcare Res Oklahoma City OK 73112 USA Southeast Univ Dept Radio Engn Nanjing 210096 Peoples R China

The electrogastrogram (EGG) is a surface measurement of gastric myoelectrical activity. The normal frequency of gastric myoelectrical activity in humans is 3 cycles/min. Abnormal frequencies in gastric myoelectrical activity have been found to be associated with functional disorders of the stomach. The aim of this article was, therefore, to develop new time-frequency analysis methods for the detection of gastric dysrhythmia from the EGG. A concept of overcomplete signal representation was used. Two algorithms were proposed for the optimization of the overcomplete signal representation. One was a fast algorithm of matching pursuit and the other was based on an evolutionary program. Computer simulations were performed to compare the performance of the proposed methods in comparison with existing time-frequency analysis methods. It was found that the proposed algorithms provide higher frequency resolution than the short time Fourier transform and Wigner-Ville distribution methods. The practical application of the developed methods to the EGG is also presented. It was concluded that these methods are well suited for the time-frequency analysis of the EGG and may also be applicable to the time-frequency analysis of other biomedical signals. (C) 1998 Biomedical Engineering Society.

关键词： spectral analysis matching pursuit stomach gastric motility electrogastrography evolutionary programming

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Integrating individual search and navigation behaviors in mechanistic movement models

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THEORETICAL ECOLOGY 2011年第3期4卷 341-355页

作者： Mueller, Thomas Fagan, William F. Grimm, Volker Univ Maryland Dept Biol College Pk MD 20742 USA Conservat Ecol Ctr Front Royal VA 22630 USA UFZ Helmholtz Ctr Environm Res Dept Ecol Modelling D-04318 Leipzig Germany

Understanding complex movement behaviors via mechanistic models is one key challenge in movement ecology. We built a theoretical simulation model using evolutionarily trained artificial neural networks (ANNs) wherein individuals evolve movement behaviors in response to resource landscapes on which they search and navigate. We distinguished among non-oriented movements in response to proximate stimuli, oriented movements utilizing perceptual cues from distant targets, and memory mechanisms that assume prior knowledge of a target's location and then tested the relevance of these three movement behaviors in relation to size of resource patches, predictability of resource landscapes, and the occurrence of movement barriers. Individuals were more efficient in locating resources under larger patch sizes and predictable landscapes when memory was advantageous. However, memory was also frequently used in unpredictable landscapes with intermediate patch sizes to systematically search the entire spatial domain, and because of this, we suggest that memory may be important in explaining super-diffusion observed in many empirical studies. The sudden imposition of movement barriers had the greatest effect under predictable landscapes and temporarily eliminated the benefits of memory. Overall, we demonstrate how movement behaviors that are linked to certain cognitive abilities can be represented by state variables in ANNs and how, by altering these state variables, the relevance of different behaviors under different spatiotemporal resource dynamics can be tested. If adapted to fit empirical movement paths, methods described here could help reveal behavioral mechanisms of real animals and predict effects of anthropogenic landscape changes on animal movement.

关键词： Individual-based models evolutionary programming Emergent behavior Animal movement Search Navigation

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Cost benefit analysis on SVC and UPFC in a dynamic economic dispatch problem

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INTERNATIONAL JOURNAL OF ENERGY SECTOR MANAGEMENT 2014年第3期8卷 395-428页

作者： Sreejith, Sekharan Simon, Sishaj P. Vellore Inst Technol Sch Elect Engn Vellore Tamil Nadu India Natl Inst Technol Dept Elect & Elect Engn Tiruchirappalli India

Purpose - The aim of this paper is to compare the performance of static VAR compensator (SVC) and unified power flow controller (UPFC) in dynamic economic dispatch (DED) problem. DED schedules the online generator outputs with the predicted load demands over a certain period so that the electric power system is operated most economically. During last decade, flexible alternating current transmission systems (FACTS) devices are broadly used for maximizing the loadability of existing power system transmission networks. However, based on the literature survey, the performance of SVC and UPFC incorporated in the DED problem and its cost-benefit analysis are not discussed earlier in any of the literature. Design/methodology/approach - Here, the DED problem is solved applying ABC algorithm incorporating SVC and UPFC. The following conditions are investigated with the incorporation of SVC and UPFC into DED problem: the role of SVC and UPFC for improving the power flow and voltage profile and the approximate analysis on cost recovery and payback period with SVC and UPFC in DED problem. Findings - The incorporation of FACTS devices reduces the generation cost and improves the stability of the system. The percentage cost recovered with FACTS devices is estimated approximately using equated monthly installment (EMI) and non-EMI scheme. It is clear from the illustrations that the installation of FACTS devices is profitable after a certain period. Research limitations/implications - In this research work, the generation cost with FACTS devices is only taken into account while calculating the profit. The other benefits like congestion management, cost gained due to land and cost due to stability issues are not considered. For future work, these things can be considered while calculating the benefit. Originality/value - The originality of the work is incorporation of FACTS devices in DED problem and approximate estimation of recovery cost with FACTS devices in DED problem.

关键词： Modeling Energy sector EMI Power flow Optimisation evolutionary programming Transmission Dynamic dispatch Cost recovery Installation cost

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Evolving continuous behaviors in the Iterated Prisoner's Dilemma

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BIOSYSTEMS 1996年第1-2期37卷 135-145页

作者： Harrald, PG Fogel, DB NAT SELECT INC LA JOLLACA 92037

evolutionary programming experiments are conducted on a variant of the Iterated Prisoner's Dilemma. Rather than assume each player having two alternative moves in the stage-game, cooperate or defect, a continuum of possible moves are available. Players' strategies are represented by feed-forward perceptrons with a single hidden layer. The population size and the number of nodes in the hidden layer are varied across a series of experiments. The results of the simulations indicate a minimum amount of complexity is required in a player's strategy in order for cooperation to evolve. Moreover, under the evolutionary dynamics of the simulation, cooperation does not appear to be a stable outcome.

关键词： evolutionary programming continuous behaviours Iterated Prisoner's Dilemma

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Comparison of different data set screening methods for use in QSAR/QSPR generation studies

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JOURNAL OF MOLECULAR STRUCTURE-THEOCHEM 2000年第1-3期507卷 229-238页

作者： Luke, BT NCI Frederick Canc Res & Dev Ctr SAIC Frederick Adv Biomed Comp Ctr Frederick MD 21702 USA

In investigations aimed at generating accurate Quantitative Structure/Activity Relationships (QSAR) or Quantitative Structure/Property Relationships (QSPR), data sets are used that potentially contain a large number of descriptors for each compound. For trample, one of the data sets generated by Breneman and Rhem [J. Comput. Chem. 18 (1997) 182-197] contain 118 descriptors and the HPLC capacity factors [log(k')] in an ODS column for 22 compounds. One method of improving the search for good relationships is to prescreen the data set and, hopefully, remove redundant descriptors. This paper examines six different methods of prescreening a data set. Each method is used to generate multiple subsets of the data, either using different screening thresholds or producing sets with a given number of descriptors. Each set is then examined in two different ways. The first uses an evolutionary programming method described earlier to generate multiple relationships, and the second determines which relationships could be obtained from this reduced set of descriptors and ranks them relative to the top 250 relationships obtained from an All Possible Sets search of the full data set. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： data set screening quantitative structure/property relationship evolutionary programming

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On-line evolutionary optimization of fuzzy control system based on decentralized population

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INTELLIGENT AUTOMATION AND SOFT COMPUTING 2000年第2期6卷 135-146页

作者： Kwon, YD Lee, JS Pohang Univ Sci & Technol Dept Elect Engn Pohang 790784 South Korea

This paper presents a real time evolutionary optimization method of the fuzzy control system by using the decentralized population technique. The presented method generates a new population for each rule of the fuzzy control system in a decentralized manner and updates each of them on-line during operation by using the normalized accelerated evolutionary programming technique. For each sampling rime, only the rules associated with the current states are updated, and thus, all of the fuzzy rules independently evolve to their optimal ones. As a result, the overall fuzzy control system evolves toward the suboptimal fuzzy control system on-line with significantly reduced evolution time. The developed optimization technique has: been applied to the mobile robot navigation problem to show its capabilities. Simulation and experimental results show the feasibility and the optimization capability of the method.

关键词： decentralized population on-line learning evolutionary programming obstacle avoidance fuzzy logic system mobile robot

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Estimating Intrinsic Formation Constants of Mineral Surface Species Using a Genetic Algorithm

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MATHEMATICAL GEOSCIENCES 2010年第1期42卷 101-127页

作者： Villegas-Jimenez, Adrian Mucci, Alfonso McGill Univ Montreal PQ H3A 2A7 Canada

The application of a powerful evolutionary optimization technique for the estimation of intrinsic formation constants describing geologically relevant adsorption reactions at mineral surfaces is introduced. We illustrate the optimization power of a simple Genetic Algorithm (GA) for forward (aqueous chemical speciation calculations) and inverse (calibration of Surface Complexation Models, SCMs) modeling problems of varying degrees of complexity, including problems where conventional deterministic derivative-based root-finding techniques such as Newton-Raphson, implemented in popular programs such as FITEQL, fail to converge or yield poor data fits upon convergence. Subject to sound a priori physical-chemical constraints, adequate solution encoding schemes, and simple GA operators, the GA conducts an exhaustive probabilistic search in a broad solution space and finds a suitable solution regardless of the input values and without requiring sophisticated GA implementations (e.g., advanced GA operators, parallel genetic programming). The drawback of the GA approach is the large number of iterations that must be performed to obtain a satisfactory solution. Nevertheless, for computationally demanding problems, the efficiency of the optimization can be greatly improved by combining heuristic GA optimization with the Newton-Raphson approach to exploit the power of deterministic techniques after the evolutionary-driven set of potential solutions has reached a suitable level of numerical viability. Despite the computational requirements of the GA, its robustness, flexibility, and simplicity make it a very powerful, alternative tool for the calibration of SCMs, a critical step in the generation of a reliable thermodynamic database describing adsorption equilibria. The latter is fundamental to the forward modeling of the adsorption behavior of minerals and geologically based adsorbents in hydro-geological settings (e.g., aquifers, pore waters, water basins) and/or in engineered

关键词： evolutionary programming Heuristic optimization Inverse modeling Surface complexation modeling and calibration Adsorption equilibria

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evolutionary METHOD OF CONSTRUCTING ARTIFICIAL INTELLIGENCE SYSTEMS

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CYBERNETICS AND SYSTEMS ANALYSIS 2019年第1期55卷 1-9页

作者： Anisimov, A. V. Marchenko, O. O. Zemlianskyi, V. R. Taras Shevchenko Natl Univ Kyiv Kiev Ukraine

An evolutionary model of constructing artificial intelligence is presented, which is destined for designing and developing intelligent systems. The model allows describing a variety of subject areas' with constructing knowledge bases. It has universal means to formally describe tasks and environments for implementing computational processes to solve them. The key basic element of the proposed model is the so-called ALF, i.e., an intelligent agent with the abilities to self-learning, communication, self-organization, and joint actions with similar agents. The development of ALF agents is based on evolutionary principles implemented using genetic algorithms. The proposed approach is implemented in the form of a game model. The developed structure and functionality of ALF agents stipulate the flexibility and efficiency of the model, which is confirmed by experiments.

关键词： artificial intelligence multiagent system evolutionary programming

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