All evolutionary algorithms experienced practitioners emphasiz the need for a careful design of the fitness function. It is commonly heard, for instance, that "If there is a bug in your fitness function, the EA w...
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In the last two decades, great progress has been made in molecular modeling through computational treatments of biological molecules grounded in evolutionary search techniques. evolutionary algorithms (EAs) are gainin...
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ISBN:
(纸本)9781450334884
In the last two decades, great progress has been made in molecular modeling through computational treatments of biological molecules grounded in evolutionary search techniques. evolutionary algorithms (EAs) are gaining popularity beyond exploring the relationship between sequence and function in biomolecules. In particular, recent work is showing the promise of EAs in exploring structure spaces of protein chains to address open problems in computational structural biology, such as de novo structure prediction and other structure modeling problems. Exploring effective interleaving of global and local search has led to hybrid EAs that are now competitive with the Monte Carlo-based frameworks that have traditionally dominated de novo structure prediction. Deeper understanding of the constraints posed by highly-coupled modular systems like proteins and integration of domain knowledge have resulted in effective reproductive operators. Multi-objective optimization has also shown promise in dealing with the conflicting terms that make up protein energy functions and effectively exploring protein energy surfaces. Combinations of these techniques have recently resulted in powerful stochastic search frameworks that go beyond de novo structure prediction and are capable of yielding comprehensive energy landscapes containing possible diverse functionally-relevant structures of proteins. The objective of this tutorial is to introduce the EC community to the rapid developments on EA-based frameworks for protein structure modeling through a concise but comprehensive review of developments in this direction over the last decade. The review will be accompanied with specific detailed highlights and interactive software demonstrations of representative methods. Building on the success and feedback of a related tutorial presented by the organizers at GECCO 2014, highlights will focus on de novo structure prediction and then energy landscape mapping of wildtype and disease-causing varia
With the rapid development of next-generation sequencing and high-throughput technologies, much biological data have been generated. The analysis of biological networks is becoming a hot topic in bioinformatics in rec...
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The Capacitated Arc Routing Problem (CARP) involves vehicles routing, serving a set of arcs in a network. This NP hard problem is extended to take into account time windows, entailing a new and hard theoretical model ...
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This text introduces a family of evolutionary algorithms named EPSO - evolutionary Particle Swarm Optimization. EPSO algorithms are evolutionary methods that borrow the movement rule from Particle Swarm Optimization m...
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Bridges are vital links in infrastructure road networks and require frequent maintenance and repair to keep them functional throughout their service lives. However, with most existing bridges being old and the funds a...
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ISBN:
(纸本)0784407940
Bridges are vital links in infrastructure road networks and require frequent maintenance and repair to keep them functional throughout their service lives. However, with most existing bridges being old and the funds available for repair being limited, the prioritization of bridges for repair, the allocation of the limited funds, and the selection of appropriate repair methods become complex optimization decisions. This is still true even when considering only one bridge component (e.g., deck) within a large network of bridges. In this paper, an integrated bridge deck management system is formulated with detailed life cycle cost analysis. The system's implementation on a spreadsheet program is briefly highlighted. Five evolutionary algorithms namely;genetic algorithms, memetic algorithms, particle swarm, ant colony systems, and shuffled frog leaping are then introduced and applied to optimize maintenance and repair decisions for various problems with different numbers of bridges. Based on the results obtained, the benefits of both the model formulation and the use of evolutionary algorithms are discussed, and the most suitable algorithm is selected for the proposed bridge deck management system. This paper contributes not only to the development of advanced management systems that can be adapted to various infrastructure types, but also to the implementation of new techniques for large scale optimization.
Hydrodynamic optimization design of the bend pipe from pump using theNavier-Stokes solver and evolutionary algorithms was conducted. The minimization of the totalpressure loss of the bend pipe was chosen as the design...
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Hydrodynamic optimization design of the bend pipe from pump using theNavier-Stokes solver and evolutionary algorithms was conducted. The minimization of the totalpressure loss of the bend pipe was chosen as the design object in order to obtain the uniform exitflows through suppressing the secondary flows. The 3-D Navier-Stokes solver was applied to evaluatethe hydrodynamic performance of the bend-pipe flows. A 7th-order Bezier curve was used toparameterize the meridional section and elliptic representation was adopted to represent thecross-section profiles of the bend pipe. evolutionary algorithms were applied in optimization. Theobtained results show that the designed bend pipe shape has much more uniform exit flows comparedwith the initial one and much weaker secondary flows, and that the evolutionary algorithms and CFDtechnique are the powerful optimization tools for the fluid machinery desiga
作者：
Oh, Jae C.EECS
Syracuse University Syracuse NY 13244 United States
This paper discusses how evolutionary algorithms are related to multi-agent systems and the possibility of military applications using the two disciplines. In particular, we present a game theoretic model for multi-ag...
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ISBN:
(纸本)0819462845
This paper discusses how evolutionary algorithms are related to multi-agent systems and the possibility of military applications using the two disciplines. In particular, we present a game theoretic model for multi-agent resource distribution and allocation where agents in the environment must help each other to survive. Each agent maintains a set of variables representing representing actual friendship and perceived friendship. The model directly addresses problems in reputation management schemes in multi-agent systems and Peer-to-Peer distributed systems. We present algorithms based on evolutionary game process for maintaining the friendship values as well as a utility equation used in each agent's decision making. For an application problem, we adapted our formal model to the military coalition support problem in peace-keeping missions. Simulation results show that efficient resource allocation and sharing with minimum communication cost is achieved without centralized control.
In this work we present a comparison of several Artificial Neural Networks weights initialization methods based on evolutionary algorithms. We have tested these methods on three datasets: KEEL regression problems, ran...
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ISBN:
(纸本)9788897999324
In this work we present a comparison of several Artificial Neural Networks weights initialization methods based on evolutionary algorithms. We have tested these methods on three datasets: KEEL regression problems, random synthetic dataset and a dataset of concentration of different chemical species from the Bioethanol To Olefins process. Results demonstrated that the tuning of neural networks initial weights improves significantly their performance compared to a random initialization. In addition, several crossover algorithms were tested to identify the best one for the present objective. In the post-hoc analysis there were found significant differences between the implemented crossover algorithms when the network has four or more inputs.
The task planning of satellite-ground time synchronization (SGTSTP) is a complex many-objective ground station scheduling problem. In this paper, we first provide a mathematical formulation of SGTSTP. To solve this pr...
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