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A CMPSO Algorithm Based Approach to Solve the Multi-plant Supply Chain Problem InTech
Felix T. S. Chan; Vikas Kumar; Nishikant Mishra.
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Tipo: 25 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/a_cmpso_algorithm_based_approach_to_solve_the_multi-plant_supply_chain_problem
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A New Ant Colony Optimization Approach for the Degree-Constrained Minimum Spanning Tree Problem Using Pruefer and Blob Codes Tree Coding InTech
Yoon-Teck Bau; Chin-Kuan Ho; Hong-Tat Ewe.
The design and implementation of Blob-coded ACO and Pr?fer-coded ACO for d-MST and lu-dMST problems have been presented. This ACO approaches is different because it constructs the encoded of the solution and can speed up computation time. Performance studies have revealed that Blob-coded ACO is almost always better than Pr?fer-coded ACO for both types of problems for the SHRD graphs. However for the d-MST problem, Blobcoded ACO does not perform better than the enhanced kruskal-ACO approach in any single
Tipo: 3 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/a_new_ant_colony_optimization_approach_for_the_degree-constrained_minimum_spanning_tree_problem_usin
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Ant Colonies for Performance Optimization of Multi-components Systems Subject to Random Failures InTech
Nabil Nahas; Mustapha Nourelfath; Daoud Ait-Kadi.
Tipo: 26 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/ant_colonies_for_performance_optimization_of_multi-components_systems_subject_to_random_failures
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Application of PSO to Design UPFC-based Stabilizers InTech
Ali T. Al-Awami; Mohammed A. Abido; Youssef L. Abdel-Magid.
In this work, the problem of enhancing the power system dynamic stability through individual and coordinated design of UPFC-based damping stabilizers has been investigated. The controllability of the electromechanical mode over a wide range of operating conditions by a given control input has been measured using a singular value decomposition-based approach. Such a study is very important as it laid the foundations of the requirements of the coordinated design problem. The stabilizer design problem has been formulated as an optimization problem with an eigenvalue-based as well as a time domain-
Tipo: 14 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/application_of_pso_to_design_upfc-based_stabilizers
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Artificial Ants in the Real World: Solving On-line Problems Using Ant Colony Optimization InTech
Bruno R. Nery; Rodrigo F. de Mello; André P. L. F. de Carvalho; Laurence T. Yang.
The behavior of real ants motivated Dorigo et al. [DMC96] to propose the Ant Colony Optimization (ACO) technique, which can be used to solve problems in dynamic environments. This technique has been successfully applied to several optimization problems [FMS05, PB05, BN06, SF06, PLF02, WGDK06, CF06, HND05]. Such results have motivated this chapter which presents ACO concepts, case studies and also a complete example on process scheduling optimization. Besides the successful adoption of ACO, it presents some relevant questions which have been motivating future directions such as: how to adjust parameters which depend on the optimization problem [SocOSj; how to reduce the execution time [G.N06, MBSD06]; the optimization improvement by using incremental local...
Tipo: 13 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/artificial_ants_in_the_real_world__solving_on-line_problems_using_ant_colony_optimization
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Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem InTech
Adil Baykasoğlu; Lale Özbakır; Pınar Tapkan.
In this study a relatively new member of swarm intelligence family that is named as "artificial bee colony" is explained in detail. Actually, different names were used in the literature for the algorithms inspired from natural honey bees. Here we prefer to use the name "artificial bee colony" to reflect population characteristic of the algorithm. A very detailed literature review along with a categorization is presented in this study. All accessible previous work on bee based optimization algorithms is tried to be reviewed. Most of the work in the literature is carried out in last two years and researchers mainly concentrated on continuous optimization and TSP problems. Previous work has presented that bee inspired algorithms have a very promising...
Tipo: 8 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/artificial_bee_colony_algorithm_and_its_application_to_generalized_assignment_problem
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Case Study Based Convergence Behaviour Analysis of ACO Applied to Optimal Design of Water Distribution Systems InTech
Aaron C. Zecchin; Holger R. Maier; Angus R. Simpson.
To gain a more complete understanding of ACO algorithms, it is important to not only consider their performance with respect to their solution quality and computational efficiency, but also the algorithms' searching behaviour. In this chapter, two statistics of searching behaviour have been considered, (i) the minimum cost found within an iteration, which is an indication of search quality, and (ii) the mean colony distance, a topological measure that describes the spread of solutions through the solution space and thus provides an indication of the degree of convergence of an algorithm. Four ACO algorithms were considered in this chapter, namely, Ant System (AS), Elitist Ant System (ASelite), Elitist-Rank Ant System (ASrank), and Max-Min Ant System...
Tipo: 24 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/case_study_based_convergence_behaviour_analysis_of_aco_applied_to_optimal_design_of_water_distributi
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Chaotic Rough Particle Swarm Optimization Algorithms InTech
Bilal Alatas; Erhan Akin.
In this chapter chaotic rough PSO, CRPSO, algorithms that use rough decision variables and rough particles that are based on notion of rough patterns have been proposed. Different chaotic maps have been embedded to adapt the parameters of PSO algorithm. This has been done by using of chaotic number generators each time a random number is needed by the classical PSO algorithm. Twelve PSO methods have been proposed and four chaotic maps have been analyzed in the data mining application. It has been detected that coupling
Tipo: 1 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/chaotic_rough_particle_swarm_optimization_algorithms
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CSV-PSO and Its Application in Geotechnical Engineering InTech
Bing-Rui Chen; Xia-Ting Feng.
Two modified versions of PSO are introduced: one is CSV-PSO algorithm in which random numbers are generated by the mixed congruential method, and another is PCSVPSO algorithm for recognizing rheological parameters of rockmass. A great deal of numerical simulations show that the CSV-PSO algorithm has better convergence performance and more accurate convergence precision, its run is more stable and it can provide certainty solution in different runtime. Sensitivity analysis of the CSV-PSO algorithm indicates that random seed, stagnancy number and constant α 0 determining flying velocity of particles have a great effect on performance of the algorithm. Proper random seed can accelerate convergence of the algorithm; while bad random seed can not only slow...
Tipo: 15 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/csv-pso_and_its_application_in_geotechnical_engineering
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Differential Meta-model and Particle Swarm Optimization InTech
Jianchao Zeng; Zhihua Cui.
This chapter introduces one uniform differential meta-model, and a new variant development for PSO combined with PID controller is proposed. The current results show it is an interesting area with the control theory to improve the performance. The future research includes incorporating some other controllers into the PSO methodology.
Tipo: 7 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/differential_meta-model_and_particle_swarm_optimization
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Distributed Particle Swarm Optimization for Structural Bayesian Network Learning InTech
Ferat Sahin; Archana Devasia.
This work involved the implementation of a highly successful technique for fault diagnosis and predictive maintenance of airplane engines. Some of the highlights of the discussed Bayesian Network approach include creation of the network without prior information and later incorporating expert information for better modeling, monitoring, and diagnosing faults in known systems, predicting faults in unknown systems, ability to handle large systems and the possibility of modifying the technique for diagnosing and distinguishing different types of faults. The presented Particle Swarm Optimization technique was effectual in reducing the computational complexity of the problem at hand by capitalizing on its innately parallel behavior thereby enabling the...
Tipo: 27 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/distributed_particle_swarm_optimization_for_structural_bayesian_network_learning
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Finite Element Mesh Decomposition Using Evolving Ant Colony Optimization InTech
Ardeshir Bahreininejad.
The application of ant colony optimization using swarm intelligence concepts, in combination with a trained feedforward neural network predictor which estimates the number of elements which will be generated within each element of the (initial) coarse mesh after mesh refinement is carried out, to the recursive bisection of finite elements meshes was described. This algorithm combines the features of the classical ant colony optimization technique with swarm intelligence to form a model which is an artificial system designed to perform a certain task. This model is used to solve the finite elements mesh recursive bisection problem which should ensure the minimum cut-size between bisections while maintaining balanced bisections. A recursive greedy algorithm...
Tipo: 9 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/finite_element_mesh_decomposition_using_evolving_ant_colony_optimization
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Hybrid Ant Colony Optimization for the Channel Assignment Problem in Wireless Communication InTech
Peng-Yeng Yin; Shan-Cheng Li.
In this chapter, we investigate the channel assignment problem (CAP) that is critical in wireless communication applications. Researchers strive to develop algorithms that are able to effectively assign limited channels to a number of cells with nonhomogeneous demands. Inspired by the recent success of metaheuristics, a hybrid ant colony optimisation (HACO) is proposed in this chapter. The HACO embodies several problem-dependent heuristics including ordering, sequential packing, and a local optimiser into an ACO framework. The advantages of this hybrid are two-fold. First, the EMC constraints can be effectively handled by the problem-dependent heuristics instead of using a penalty function as observed in other works which may lengthen the elapsed time in...
Tipo: 23 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/hybrid_ant_colony_optimization_for_the_channel_assignment_problem_in_wireless_communication
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Hybrid Optimisation Method for the Facility Layout Problem InTech
Yasmina Hani; Lionel Amodeo; Farouk Yalaoui; Haoxun Chen.
We have proposed a robust meta-heuristic algorithm for the layout problem modelled as a QAP. The algorithm is based on ant colony algorithm combined with a guided local search, and it uses an augmented cost function in order to guide the local search out of a local optimum. The performance of the proposed algorithm was also evaluated on a number of benchmark problems selected from the literature and compared with other heuristics developed for the facility layout problem as well as other algorithms recently developed for the QAP. The experimental results reveal that the proposed algorithm is effective and efficient for the facility layout problem considered. Other heuristic algorithms for the FLP shall be devised, tested, and compared with our algorithm in...
Tipo: 18 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/hybrid_optimisation_method_for_the_facility_layout_problem
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Integration Method of Ant Colony Algorithm and Rough Set Theory for Simultaneous Real Value Attribute Discretization and Attribute Reduction InTech
Yijun He; Dezhao Chen; Weixiang Zhao.
In this study, ant colony algorithm is proposed for simultaneous real value attributes discretization and reduction. Based on the concept of distinction table in rough set theory, the relationship between discretization and reduction is discussed, and these two different problems can be integrated into a unified framework. Moreover, the relationship between this unified framework and set covering problem is analyzed. The detailed strategy for ant colony algorithm to solve this problem is proposed and applied to the four datasets. The obtained results demonstrate the effectiveness of the proposed method, showing the better performance than those of the other three rough set theory based heuristic methods. However, this is a preliminary study, because we...
Tipo: 2 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/integration_method_of_ant_colony_algorithm_and_rough_set_theory_for_simultaneous_real_value_attribut
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Job-shop Scheduling and Visibility Studies with a Hybrid ACO Algorithm InTech
Heinonen; J.; Pettersson; F..
When paired with the local search the ACO produces noteworthy results very fast (typically 5% from optimum within 200 rounds of calculations). The Max-Min Ant System outperformed all other ACO versions, and it did so for all types of visibility tested, showing that it is indeed a leading candidate for choosing your ant system. There are various version of ACO available and this chapter served its purpose to both do an attempt at ranking them, showing the impact of various visibility methods as well as proving that pure ACO methods produce good results, but even better when combined with the postprocessing algorithm shown. Naturally, not every combination of ACO and a local search is guaranteed to work better than a pure ACO, but a hybrid version can...
Tipo: 20 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/job-shop_scheduling_and_visibility_studies_with_a_hybrid_aco_algorithm
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Particle Swarm Optimization for Simultaneous Optimization of Design and Machining Tolerances InTech
Liang Gao; Chi Zhou; Kun Zan.
Tolerance assignment is very important in product design and machining. The conventional sequentially tolerance allocation suffers from several drawbacks. Therefore, a simultaneous tolerance assignment approach is adopted to overcome these drawbacks. However, the optimization task is usually difficult to tackle due to the nonlinear, multi-variable and high constrained characteristics. In trying to solve such constrained optimization problem, penalty function based methods have been the most popular approach. However, since the penalty function approach is generic and applicable to any type of constraint, their performance is not always satisfactory and consistent. In view of the memory characteristics of PSO, a new constraints handling strategy suit for...
Tipo: 17 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/particle_swarm_optimization_for_simultaneous_optimization_of_design_and_machining_tolerances
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Particle Swarm Optimization in Structural Design InTech
Ruben E. Perez; Kamran Behdinan.
Particle Swarm Optimization is a population-based algorithm, which mimics the social behaviour of animals in a flock. It makes use of individual and group memory to update each particle position allowing global as well as local search optimization. Analytically the PSO behaves similarly to a traditional line-search where the step length and search direction are stochastic. Furthermore, it was shown that the PSO search strategy can be represented as a discrete-dynamic system which converges to an equilibrium point. From a stability analysis of such system, a parameter selection heuristic was developed which provides an initial guideline to the selection of the different PSO setting parameters. Experimentally, it was found that using the derived heuristics...
Tipo: 21 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/particle_swarm_optimization_in_structural_design
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Particle Swarm Optimization - Stochastic Trajectory Analysis and Parameter Selection InTech
M. Jiang; Y. P. Luo; S. Y. Yang.
The stochastic process theory is applied to analyze the particle swarm optimization algorithm determined by five-dimensional real-value parameter tuple { , c1, c2, a, b}, considering the randomness thoroughly. Specifically speaking, stochastic convergence analysis is conducted on PSO algorithm when it is in stagnation phase, and the convergent properties of expectation and variance sequence of particle's position are studied. The analysis results determines corresponding parameter ranges, both in formular and graphical form. This result is helpful to understand the mechanism of PSO algorithm and select appropriate parameters to make PSO algorithm more powerful. After the theoretical stochastic convergence analysis of PSO algorithm in stagnation phase,...
Tipo: 11 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/particle_swarm_optimization_-_stochastic_trajectory_analysis_and_parameter_selection
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Power Plant Maintenance Scheduling Using Ant Colony Optimization InTech
Wai Kuan Foong; Holger Robert Maier; Angus Ross Simpson.
In this chapter, a formulation for applying Ant Colony Optimization (ACO) to power plant maintenance scheduling optimization (PPMSO) has been developed and successfully tested using four case studies (original and modified versions of two benchmark case studies from the literature). In particular, the performance of the heuristic formulation developed, the two local search algorithms introduced and the overall utility of the ACO-PPMSO formulation were investigated. The results obtained have shown that the heuristic formulation improves the performance of the ACO-PPMSO algorithm significantly when applied to the four case studies investigated. It was found that while the PPMSO-2-opt local search operator seems to work well for unconstrained problems, it is...
Tipo: 16 Palavras-chave: Swarm Intelligence; Focus on Ant and Particle Swarm Optimization.
Ano: 2007 URL: http://www.intechopen.com/articles/show/title/power_plant_maintenance_scheduling_using_ant_colony_optimization
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