By Topic

# Evolutionary Computation, 1997., IEEE International Conference on

## Filter Results

Displaying Results 1 - 25 of 129
• ### Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)

Publication Year: 1997
| PDF (670 KB)
• ### Genetic algorithms for solving shortest path problems

Publication Year: 1997, Page(s):401 - 406
Cited by:  Papers (31)
| | PDF (621 KB)

In this study, we investigated the possibility of using genetic algorithms to solve shortest path problems. The most thorny and critical task for developing a genetic algorithm to this problem is how to encode a path in a graph into a chromosome. A priority-based encoding method is proposed which can potentially represent all possible paths in a graph. Because a variety of network optimization pro... View full abstract»

• ### Random Keys Genetic Algorithm With Adaptive Penalty Function For Optimization Of Constrained Facility Layout Problems

Publication Year: 1997, Page(s):407 - 411
Cited by:  Papers (1)
| | PDF (481 KB)

First Page of the Article
View full abstract»

• ### Author index

Publication Year: 1997, Page(s):721 - 724
| PDF (130 KB)
• ### Evolutionary search guided by the constraint network to solve CSP

Publication Year: 1997, Page(s):337 - 342
Cited by:  Papers (9)
| | PDF (552 KB)

We are interested in defining a general evolutionary algorithm to solve constraint satisfaction problems, which takes into account both advantages of the systematic and traditional methods and of characteristics of the CSP. In this context knowledge about properties of the constraint network has allowed us to define a fitness function, for evaluation (Riff, 1996). We introduce two new operators wh... View full abstract»

• ### Coevolutionary instability in games: an analysis based on genetic algorithms

Publication Year: 1997, Page(s):703 - 708
| | PDF (544 KB)

Recently, genetic algorithms have been extensively applied to modeling bounded rationality in game theory. While these applications advance our understanding or game theory, they have generated some new phenomena which have not been well treated in conventional game theory. We systemize the study of one of these new phenomena, namely, coevolutionary instability. We exemplify the basic properties o... View full abstract»

• ### Solving optimal control problems with a cost changing control by evolutionary algorithms

Publication Year: 1997, Page(s):331 - 336
Cited by:  Papers (2)
| | PDF (544 KB)

Many mathematical solutions to certain classes of optimal control problems, particularly problems which give rise to chattering controls', make some physically unrealistic assumptions in order to solve the problems. These solutions often ignore the cost of changing control and thus fail to give physically realistic results due to the physical reality of this cost in many applications. When this c... View full abstract»

• ### Influencing parameters of evolutionary algorithms for sequencing problems

Publication Year: 1997, Page(s):575 - 580
Cited by:  Papers (1)
| | PDF (548 KB)

Several problems in computer aided design (CAD) of integrated circuits (ICs) have to solve sequencing problems. For this reason many algorithms for solving these problems have been proposed. Especially, evolutionary algorithms (EAs) have been successfully applied in the past in these areas. We study the influence of different parameters on run time and quality for one specific problem of large pra... View full abstract»

• ### Monitoring and interpreting evolved behaviours in an oligopoly

Publication Year: 1997, Page(s):697 - 701
| | PDF (372 KB)

In a marketplace competition, participants develop strategies to maximise their returns. These strategies are based on the participants' knowledge and beliefs of the marketplace. For instance, in an oligopolistic marketplace, participants may know the relativity of their product's price with respect to other participants and believe that this relativity and its history critically influences their ... View full abstract»

• ### Speeding-up adaptive heuristic critic learning with FPGA-based unsupervised clustering

Publication Year: 1997, Page(s):685 - 689
| | PDF (412 KB)

Neurocontrol is a crucial area of fundamental research within the neural network field. Adaptive heuristic critic learning is a key algorithm for real-time adaptation in neurocontrollers. In this paper, we show how an unsupervised neural network model with an adaptable structure can be used to speed-up adaptive heuristic critic learning, present its FPGA design, and show how it adapts the neurocon... View full abstract»

• ### The emergence of insect protandry: a “natural” evolutionary computation application

Publication Year: 1997, Page(s):325 - 330
| | PDF (452 KB)

When resources and their consumers have matching distributions in space or time, an ideal free distribution (IFD) is achieved, whereby each consumer receives the same amount of resource. In nature, both spatial and temporal IFDs are commonplace, with protandry in insects providing a popular textbook example of the latter. This research uses individual based population models and genetic algorithms... View full abstract»

• ### Distance functions for order-based encodings

Publication Year: 1997, Page(s):49 - 54
Cited by:  Papers (4)
| | PDF (648 KB)

Distance functions permeate the field of genetic algorithms especially in relation to mating strategies, incest prevention, diversity preservation, and techniques that find multiple solutions. Distance functions can be found in the literature for genotypes which use binary or numerical parameter encodings. Various phenotypic distance functions that act on the properties of the decoded genotype hav... View full abstract»

• ### Exogenous parameter selection in a real-valued genetic algorithm

Publication Year: 1997, Page(s):569 - 574
| | PDF (624 KB)

To evaluate the performance of a real valued genetic algorithm (GA) exploiting domain knowledge, we systematically evaluate the effect of exogenous parameters using analysis of variance. The GA platform used for this study is Genocop-III, a real valued, co evolutionary algorithm implementation for numerical optimization. We use the protein structure prediction (PSP) problem as our test domain. Nea... View full abstract»

• ### A society of hill-climbers

Publication Year: 1997, Page(s):319 - 324
Cited by:  Papers (9)
| | PDF (616 KB)

The paper is concerned with function optimisation in binary search spaces. It focuses on how hill climbers can work together and/or use their past trials in order to speed up the search. A hill climber is viewed as a set of mutations. The challenge is twofold: one must determine how many bits should be mutated, and which bits should preferably be mutated, or in other words, which climbing directio... View full abstract»

• ### Decision making in a hybrid genetic algorithm

Publication Year: 1997, Page(s):121 - 125
Cited by:  Papers (16)
| | PDF (480 KB)

There are several issues that need to be taken into consideration when designing a hybrid problem solver. The paper focuses on one of them-decision making. More specifically, we address the following questions: given two different methods, how to get the most out of both of them? When should we use one and when should we use the other in order to get maximum efficiency? We present a model for hybr... View full abstract»

• ### Knowledge-based self-adaptation in evolutionary programming using cultural algorithms

Publication Year: 1997, Page(s):71 - 76
Cited by:  Papers (18)
| | PDF (460 KB)

We investigate knowledge-based self-adaptation in evolutionary programming (EP) using cultural algorithms for 22 function optimization problems. The results suggest that the use of a cultural framework for self-adaptation in EP can produce substantial performance improvements as expressed in terms of CPU time. The nature of these improvements and the type of knowledge that is most effective in pro... View full abstract»

• ### Robust encodings in genetic algorithms: a survey of encoding issues

Publication Year: 1997, Page(s):43 - 48
Cited by:  Papers (8)
| | PDF (668 KB)

Problems of encoding brittleness have been observed in the genetic algorithm (GA) literature, where slightly different problems require completely different genetic encodings for good solutions to be found. As research continues into GA encoding schemes the idea of encoding robustness becomes more important. A robust encoding is one which will be effective for a wide range of problem instances tha... View full abstract»

• ### A decision aid for theater missile defense

Publication Year: 1997, Page(s):563 - 568
Cited by:  Papers (4)  |  Patents (1)
| | PDF (740 KB)

The Theater Missile Defense Problem of placing interceptor batteries to defend assets against an intermediate range ballistic missile threat is formulated as a constrained optimization problem. Discontinuities and the existence of many local minima prevent the application of gradient based optimization techniques. A genetic algorithm is employed to overcome these features of the problem. Implement... View full abstract»

• ### Stepping stones and hidden haystacks: when a genetic algorithm defeats a hillclimber

Publication Year: 1997, Page(s):139 - 142
| | PDF (456 KB)

Following intuitive notions on gross aspects of how a GA behaves, we are able to demonstrate how to construct functions on which a GA will greatly outperform a hillclimber. This augments related work on long path problems, and gene switch cost functions, which describe similarly GA appropriate' landscapes but on rather less intuitively clear grounds. Although artificial, the construction of these... View full abstract»

• ### An evolutionary heuristic for knowledge base partitioning problem

Publication Year: 1997, Page(s):657 - 662
| | PDF (416 KB)

In this paper, I have tried to give an evolutionary heuristic to the knowledge base partitioning problem, which is a well-known NP-complete problem. There are different heuristics already existing to this end. After proposing my scheme, I make a comparative study in relation to the relative performance of my scheme vis-a`-vis an existing genetic algorithm on the same benchmark. I show how my... View full abstract»

• ### A scatter search based approach for the quadratic assignment problem

Publication Year: 1997, Page(s):165 - 169
Cited by:  Papers (5)
| | PDF (428 KB)

Scatter search is an evolutionary heuristic, proposed two decades ago, that uses linear combinations of a population subset to create new solutions. A special operator is used to ensure their feasibility and to improve their quality. The authors propose a scatter search approach to the QAP problem. The basic method is extended with intensification and diversification stages and they present a proc... View full abstract»

• ### Application of an evolution strategy to the Hopfield model of associative memory

Publication Year: 1997, Page(s):679 - 683
Cited by:  Papers (2)
| | PDF (388 KB)

We apply evolutionary computations to Hopfield's neural network model of associative memory. In the Hopfield model, an almost infinite number of combinations of synaptic weights gives a network an associative memory function. Furthermore, there is a trade-off between the storage capacity and the size of the basin of attraction. Therefore, the model can be thought of as a test suite of multi-modal ... View full abstract»

• ### Herby: an evolutionary artificial ecology

Publication Year: 1997, Page(s):315 - 318
Cited by:  Papers (1)
| | PDF (364 KB)

The paper outlines the design and implementation of an artificial ecology for the investigation of hypotheses relating to real ecologies. An individual based model is used where the differences between individuals provide the basis for selection View full abstract»

• ### New parallel hybrid genetic algorithm based on molecular dynamics approach for energy minimization of atomistic systems

Publication Year: 1997, Page(s):115 - 119
Cited by:  Patents (1)
| | PDF (368 KB)

A hybrid genetic algorithm (HGA) for the optimization of the ground state structure of a metallic atomic cluster has been implemented on a MIMD-SIMD parallel platform. The concept of building block (BB) is generalized to cover this real coded optimization problem. On the basis of some reasonings on the dependence of the convergence of genetic algorithms (GAs) from BBs, a hybrid genetic algorithm (... View full abstract»

• ### Evolutionary fuzzy modeling using fuzzy neural networks and genetic algorithm

Publication Year: 1997, Page(s):623 - 627
Cited by:  Papers (9)  |  Patents (4)
| | PDF (356 KB)

Fuzzy modeling is one of the promising methods for describing nonlinear systems. The determination of the antecedent structure of the fuzzy model, i.e. input variables and the number of membership functions for the inputs, has been one of the most important problems of fuzzy modeling. The authors propose a hierarchical fuzzy modeling method using fuzzy neural networks (FNN) and a genetic algorithm... View full abstract»