Evolutionary Computation, 1997., IEEE International Conference on

13-16 April 1997

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  • Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)

    Publication Year: 1997
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    Freely Available from IEEE
  • Genetic algorithms for solving shortest path problems

    Publication Year: 1997, Page(s):401 - 406
    Cited by:  Papers (32)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • 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)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (481 KB)

    First Page of the Article
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  • Author index

    Publication Year: 1997, Page(s):721 - 724
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    Freely Available from IEEE
  • Evolutionary search guided by the constraint network to solve CSP

    Publication Year: 1997, Page(s):337 - 342
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • A neural network that uses evolutionary learning

    Publication Year: 1997, Page(s):635 - 639
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (500 KB)

    This paper proposes a new neural architecture (Nessy) which uses evolutionary optimization for learning. The architecture, the outline of its evolutionary algorithm and the learning laws are given. Nessy is based on several modifications of the multilayer backpropagation neural network. The neurons represent genes of evolutionary optimization, referred to as solutions. Weights represent probabilit... View full abstract»

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  • Exogenous parameter selection in a real-valued genetic algorithm

    Publication Year: 1997, Page(s):569 - 574
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • On the use of niching for dynamic landscapes

    Publication Year: 1997, Page(s):361 - 366
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (596 KB)

    Application of genetic algorithms to problems where the fitness landscape changes dynamically is a challenging problem. Genetic algorithms for such environments must maintain a diverse population that can adapt to the changing landscape and locate better solutions dynamically. A niching genetic algorithm suitable for locating multiple solutions in a multimodal landscape is applied. The results sho... View full abstract»

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  • MAX-MIN Ant System and local search for the traveling salesman problem

    Publication Year: 1997, Page(s):309 - 314
    Cited by:  Papers (175)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (668 KB)

    Ant System is a general purpose algorithm inspired by the study of the behavior of ant colonies. It is based on a cooperative search paradigm that is applicable to the solution of combinatorial optimization problems. We introduce MAX-MIN Ant System, an improved version of basic Ant System, and report our results for its application to symmetric and asymmetric instances of the well known traveling ... View full abstract»

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

    Publication Year: 1997, Page(s):331 - 336
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • A multi-sexual genetic algorithm for multiobjective optimization

    Publication Year: 1997, Page(s):59 - 64
    Cited by:  Papers (20)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (368 KB)

    In this paper a new method for solving multicriteria optimization problems by Genetic Algorithms is proposed. Standard Genetic Algorithms use a population, where each individual has the same sex (or has no sex) and any two individuals can be crossed over. In the proposed Multisexual Genetic Algorithm (MSGA), individuals have an additional feature, their sex or gender and one individual from each s... View full abstract»

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  • Decision making in a hybrid genetic algorithm

    Publication Year: 1997, Page(s):121 - 125
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • A decision aid for theater missile defense

    Publication Year: 1997, Page(s):563 - 568
    Cited by:  Papers (4)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • Generation of optimal fault tolerant locomotion of the hexapod robot over rough terrain using evolutionary programming

    Publication Year: 1997, Page(s):489 - 494
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (468 KB)

    Extends the authors' previous (1996) results on optimal fault-tolerant locomotion of the hexapod walking robot over even terrain by generalizing the shape of the ground. A method of searching for the optimal or near-optimal fault-tolerant sequence of free gaits over rough terrain using evolutionary programming is proposed. Based on the sequence of gaits derived on the even terrain, the proposed al... View full abstract»

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  • Learning the local search range for genetic optimisation in nonstationary environments

    Publication Year: 1997, Page(s):355 - 360
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (524 KB)

    We examine a modification to the genetic algorithm. The variable local search (VLS) operator was designed to enable the genetic algorithm based online optimisers to track optima of time-varying dynamic systems. This feature is not to the detriment of its ability to provide sound results for the stationary environments. The operator matches the level of diversity introduced into the population with... View full abstract»

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  • The particle swarm: social adaptation of knowledge

    Publication Year: 1997, Page(s):303 - 308
    Cited by:  Papers (492)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (524 KB)

    Particle swarm adaptation is an optimization paradigm that simulates the ability of human societies to process knowledge. The algorithm models the exploration of a problem space by a population of individuals; individuals' successes influence their searches and those of their peers. The algorithm is relevant to cognition, in particular the representation of schematic knowledge in neural networks. ... View full abstract»

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

    Publication Year: 1997, Page(s):325 - 330
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • The importance of maintaining behavioural link between parents and offspring

    Publication Year: 1997, Page(s):629 - 633
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (376 KB)

    In a study of evolutionary artificial neural networks (Yao and Liu, 1996), it has been argued that a partial training process after an architectural mutation plays an important role in maintaining the behavioural link between parents and their offspring and thus is beneficial to the simulated evolution. This paper investigates the issue further through a number of experiments. The experimental res... View full abstract»

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  • Genetic design of analog IIR filters with variable time delays for optically controlled microwave signal processors

    Publication Year: 1997, Page(s):437 - 442
    Cited by:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (516 KB)

    This paper presents the application of genetic algorithms to the design of analog IIR filters with variable time delays-specific examples for tunable optically controlled microwave signal processors. In addition to the IIR filter coefficients as the standard design parameters, the time delays can be optimized. Because of physical constraints, specific restrictions of the design parameters, however... View full abstract»

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  • A method for chromosome handling of r-permutations of n-element set in genetic algorithms

    Publication Year: 1997, Page(s):55 - 58
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (292 KB)

    Combinatorial optimisation problems are in the domain of Genetic Algorithms (GA) interest. Unfortunately ordinary crossover and mutation operators cause problems for chromosome representations of permutations and some types of combinations. This is so because offsprings generated by means of the ordinary operators are of a great possibility no more valid chromosomes. A variety of methods and new o... View full abstract»

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  • The firefly machine: online evolware

    Publication Year: 1997, Page(s):181 - 186
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (704 KB)

    We present the firefly machine, an evolving hardware system, demonstrating that “evolving ware” (or “evolware”) can be attained. The system is based on the cellular programming approach, in which parallel cellular machines evolve to solve computational tasks. The firefly system operates with no reference to an external device, such as a computer that carries out genetic ope... View full abstract»

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  • A self-organizing system with cell-specialization

    Publication Year: 1997, Page(s):279 - 284
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (472 KB)

    For the study of evolutionary systems, we have already proposed several models. In this paper, we are concerned with a different type of evolutionary system, the cell-specialization. As seen in hydras, cell-specialization is one of the very important types of self-organization. In the process of cell-specialization, each cell which has the same DNA is specialized. The whole system which consists o... View full abstract»

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  • 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:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (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»

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  • Differential evolution vs. the functions of the 2nd ICEO

    Publication Year: 1997, Page(s):153 - 157
    Cited by:  Papers (29)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (388 KB)

    Differential evolution (DE) is a simple evolutionary algorithm for numerical optimization whose most novel feature is that it mutates vectors by adding weighted, random vector differentials to them. A new version of the DE algorithm is described and the results of its attempts to optimize the 7 real-valued functions of the 2nd ICEO are tabulated. DE succeeded in finding each function's ... View full abstract»

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  • DNA computing based on chaos

    Publication Year: 1997, Page(s):255 - 260
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB)

    In this paper a new approach for the realization of the DNA computing paradigm is presented. It exploits the natural richness of chaotic dynamics to efficiently generate and process coded binary sequences following the DNA computing framework introduced by Adleman (1994). The new method is discussed and some simulation results regarding the Directed Hamiltonian Path problem are presented View full abstract»

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