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Title Particle swarm optimization : theory, techniques, and applications / Andrea E. Olsson, editor
Published Hauppauge, N.Y. : Nova Science Publishers, c2011

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Description 1 online resource
Series Engineering tools, techniques and tables
Engineering tools, techniques and tables.
Contents PARTICLE SWARM OPTIMIZATION: THEORY, TECHNIQUES AND APPLICATIONS; PARTICLE SWARM OPTIMIZATION: THEORY, TECHNIQUES AND APPLICATIONS ; CONTENTS ; PREFACE ; USING MONO-OBJECTIVE AND MULTI-OBJECTIVEPARTICLE SWARM OPTIMIZATION FOR THE TUNINGOF PROCESS CONTROL LAWS; Abstract; I. Introduction; II. Choice for the Use of Particle Swarm Optimization; III. Mono-objective PSO for the Design of Control Laws; III. 1. Definition of Optimization Problems; III. 2. Tuning of PID Controllers; III. 3. Reduced Order H Control; III. 3.1. H Control; III. 3.2. Full Order H Synthesis
III. 3.3. Reduced Order H SynthesisIII. 3.4. Case Study; III. 3.5. One Output H Synthesis; III. 3.6. Three Output H Synthesis; III. 4. Non Linear Predictive Control; IV. Multi-objective PSO for the Design of Controllers; V. Conclusions; References; STUDY ON VEHICLE ROUTING PROBLEM WITH TIMEWINDOWS BASED ON ENHANCED PARTICLESWARM OPTIMIZATION APPROACH; Abstract; 1. Introduction; 2. Problem Solving Methodology; 2.1. The Basic Particle Swarm Optimization; 2.2. The Vehicle Routing Problem with Time Windows Problem; 2.3. The Difficulty for Using Basic PSO to Solve the VRPTW
2.4. The New Solution Strategies of Predicting Particle Swarm OptimizationStrategy I: Search Space Transformation; Strategy II: Boundary Constraint Handling; Strategy III: Forward Predicting Update on Velocity Update Equation; 3. The Algorithm of Predicting PSO; Phase I: Candidate Customer Search in Initial Stage; Phase II: Global Initial Solution Generated Through Feasibility Test; Phase III. Population Search for Optimization; 4. Computational Experiment; 4.1. Problem Data; 4.2. Computational Results; 5. Conclusion; Reference
RELIABILITY OPTIMIZATION PROBLEMS USINGADAPTIVE GENETIC ALGORITHM AND IMPROVEDPARTICLE SWARM OPTIMIZATIONAbstract; 1. Introduction; 2. Reliability Optimization Problems; 3. Hybrid Approach Using iGA and iPSO; 3.1. iGA Design; 3.2. iPSO Design; 3.3. Hybrid Approach; 3.4. Overall Procedure; 4. Numerical Examples; 4.1. Test Problems; 4.1.1. Test Problem 1 (T-1); 1) Case 1; 2) Case 2; 3) Case 3; 4.1.2. Test Problem 2 (T-2); 4.2. Test Results; 5. Conclusion; References; CONVERGENCE ISSUES IN PARTICLESWARM OPTIMIZATION; Abstract; Introduction; Managing Population and Exploration
Managing Velocity and Search RegionManaging Optima and Resuming Exploration; Convergence in Optimization Algorithms Otherthan PSO -- Overview; Convergence Analysis and Discussion; Terminology; Convergence as a Stopping Condtion; Conclusion; Convergence Methods; Guidelines for Convergence; MAV Convergence/Stopping Point Pseudo-Code; Unimodal Problems; Multimodal Problems; Epilogue; References; GLOBALLY CONVERGENT MODIFICATIONS OF PARTICLE SWARM OPTIMIZATION FOR UNCONSTRAINED OPTIMIZATION; Abstract; 1. Introduction; 2.A Generalized Scheme for PSO; 3. Issues on the Parameters Assessment in PSO
Bibliography Includes bibliographical references and index
Notes English
Description based on print version record and CIP data provided by publisher
Subject Swarm intelligence.
Mathematical optimization.
COMPUTERS -- Enterprise Applications -- Business Intelligence Tools.
COMPUTERS -- Intelligence (AI) & Semantics.
Mathematical optimization
Swarm intelligence
Form Electronic book
Author Olsson, Andrea E
LC no. 2020676742
ISBN 9781613247006
1613247001