There are several search algorithms for the shortest path problem: the Dijkstra algorithm and Bellman-Ford algorithm, to name a few. These algorithms are not effective for dynamic traffic network involving rapidly cha...
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ISBN:
(纸本)9783540773672
There are several search algorithms for the shortest path problem: the Dijkstra algorithm and Bellman-Ford algorithm, to name a few. These algorithms are not effective for dynamic traffic network involving rapidly changing travel time. The evolution program is useful for practical purposes to obtain approximate solutions for dynamic route guidance systems (DRGS). The objective of this paper is to propose an adaptive routing algorithm using evolution program (ARAEP) that is to find the multiple shortest paths within limited time when the complexity of traffic network including turn-restrictions, U-turns, and P-turns exceeds a predefined threshold.
The response time variability problem (RTVP) is a hard scheduling problem that has recently been defined in the literature and has a wide range of real-world applications in mixed-model assembly lines, multithreaded c...
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The response time variability problem (RTVP) is a hard scheduling problem that has recently been defined in the literature and has a wide range of real-world applications in mixed-model assembly lines, multithreaded computer Systems, network environments and others. The RTVP arises whenever products, clients or jobs need to be sequenced in such a way that the variability in the time between the points at which they receive the necessary resources is minimized. Since the RTVP is a complex problem, heuristic and metaheuristic techniques are needed to solve it. The best results in the literature for the RTVP have been obtained with a psychoclonal algorithm. We propose a genetic algorithm (CA) that is adapted to solve the RTVP. A computational experiment is carried out and it is shown that, on average, the CA produces better results than the psychoclonal algorithm. (C) 2009 Elsevier B.V. All rights reserved.
A goal of geophysical inversion is to find all earth models which, when operated upon by some forward method, produce synthetic data that gives an acceptable agreement with observed data. Unfortunately, most inverse p...
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ISBN:
(纸本)1880132974
A goal of geophysical inversion is to find all earth models which, when operated upon by some forward method, produce synthetic data that gives an acceptable agreement with observed data. Unfortunately, most inverse problems in geophysics are non-linear and poorly constrained. Conventional procedures of Rayleigh wave inversion have many shortcomings such as only roughly defining the initial model with poor inversion reliability, strong inversion subjectivity and unsatisfactory inversion results. Hunaidi (1998) proposed the method of genetic algorithm based on evolution law. His method has not overcome the restriction of inversion layer number, but provides us an idea on how to solve the problem: finding genetic algorithm adapting to the Rayleigh waves inversion. In this paper, the application of optimized genetic algorithm-evolution program, to fundamental Rayleigh waves inversion is introduced. The new method of uniform thickness layered inversion of dispersion function and optimized objective function and population of genetic algorithm is proposed. The results of theoretical models and field data show that, in contrast to traditional linear inversion methods and genetic algorithm, evolution program to Rayleigh waves inversion effectively overcomes the limitation of inversion parameter number and improves the stability of the solutions.
The main goal of this article is to present a strategy how to deal with multidimensional environmental data sets containing outliers. For calibration purposes we recommend the robust Partial Least Squares (rPLS) metho...
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The main goal of this article is to present a strategy how to deal with multidimensional environmental data sets containing outliers. For calibration purposes we recommend the robust Partial Least Squares (rPLS) method, which can well describe data majority not influenced by outlying observations. This method is used to describe quantitative relationships between concentration profiles of metals measured for sediments and the parameters analyzed in water in the Saale river.
This paper presents an evolution program for deterministic and stochastic optimizations. To overcome premature convergence and stalling of the solution, we suggest an exponential-fitness scaling scheme. To avoid the c...
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This paper presents an evolution program for deterministic and stochastic optimizations. To overcome premature convergence and stalling of the solution, we suggest an exponential-fitness scaling scheme. To avoid the chromosomes jamming into a corner, we introduce mutation-1 which mutates the chromosomes in a free direction. To improve the chromosomes, we introduce mutation-1 which mutates the chromosomes in the gradient direction or its negative, according to the kind of problem. Monte Carlo simulation will be employed to solve the multiple integral which is the most difficult task in the stochastic optimization. Finally, some numerical examples are discussed.
Goal programming (GP) is one of powerful techniques for solving multi-objective optimization and has been applied to various real-life problems. This paper presents an evolution program for solving nonlinear goal prog...
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Goal programming (GP) is one of powerful techniques for solving multi-objective optimization and has been applied to various real-life problems. This paper presents an evolution program for solving nonlinear goal programming problems.
Tile Bicriteria Linear Transportation Problem (BLTP) is a special structure of the multiobjective transportation problem since the feasible region can be depicted in two dimensions in criteria space. In this paper, we...
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Tile Bicriteria Linear Transportation Problem (BLTP) is a special structure of the multiobjective transportation problem since the feasible region can be depicted in two dimensions in criteria space. In this paper, we present an evolution program to solve the bicriteria transportation problem In this method, an improved selection strategy is included and a particular technique called Extinction and Immigration is used for crossover operator when the same chromosomes are chosen to mate. A set of efficient solutions or an approximation of this set can be found by this approach.
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