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Evolutionary Optimization

Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques...

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Bibliographic Details
Main Authors: Sarker, Ruhul. (Author), Mohammadian, Masoud. (Author), Yao, Xin. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: Boston, MA : Springer US, 2002.
Series:International Series in Operations Research & Management Science, 48
Subjects:
Business.
Leadership.
Operations research.
Decision making.
Artificial intelligence.
Mathematical optimization.
Calculus of variations.
Business and Management.
Business Strategy/Leadership.
Operation Research/Decision Theory.
Optimization.
Calculus of Variations and Optimal Control; Optimization.
Artificial Intelligence (incl. Robotics).
Online Access:View fulltext via EzAccess
Table of Contents:
  • Conventional Optimization Techniques
  • Evolutionary Computation
  • Single Objective Optimization
  • Evolutionary Algorithms and Constrained Optimization
  • Constrained Evolutionary Optimization
  • Multi-Objective Optimization
  • Evolutionary Multi-Objective Optimization: A Critical Review
  • Multi-Objective Evolutionary Algorithms for Engineering Shape Design
  • Assessment Methodologies for Multiobjective Evolutionary Algorithms
  • Hybrid Algorithms
  • Utilizing Hybrid Genetic Algorithms
  • Using Evolutionary Algorithms to Solve Problems by Combining Choices of Heuristics
  • Constrained Genetic Algorithms and Their Applications in Nonlinear Constrained Optimization
  • Parameter Selection in EAs
  • Parameter Selection
  • Application of EAs to Practical Problems
  • Design of Production Facilities Using Evolutionary Computing
  • Virtual Population and Acceleration Techniques for Evolutionary Power Flow Calculation in Power Systems
  • Application of EAs to Theoretical Problems
  • Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions
  • A Genetic Algorithm Heuristic for Finite Horizon Partially Observed Markov Decision Problems
  • Using Genetic Algorithms to Find Good K-Tree Subgraphs.

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