Genetic Algorithms:
A Tutorial
“Genetic Algorithms are
good at taking large,
potentially huge search
spaces and navigating
them, looking for optimal
combinations of things,
solutions you might not
otherwise find in a
lifetime.”
- Salvatore Mangano
Computer Design, May 1995
,The Genetic Algorithm
• Directed search algorithms based on the mechanics of biological
evolution
• Developed by John Holland, University of Michigan (1970’s)
• To understand the adaptive processes of natural systems
• To design artificial systems software that retains the robustness of natural
systems
,The Genetic Algorithm (cont.)
• Provide efficient, effective techniques for optimization and machine
learning applications
• Widely-used today in business, scientific and engineering circles
, Classes of Search Techniques
Search techniques
Calculus-based techniques Guided random search techniques Enumerative techniques
Direct methods Indirect methods Evolutionary algorithms Simulated annealing Dynamic programming
Finonacci Newton Evolutionary strategies Genetic algorithms
Parallel Sequential
Centralized Distributed Steady-state Generational
A Tutorial
“Genetic Algorithms are
good at taking large,
potentially huge search
spaces and navigating
them, looking for optimal
combinations of things,
solutions you might not
otherwise find in a
lifetime.”
- Salvatore Mangano
Computer Design, May 1995
,The Genetic Algorithm
• Directed search algorithms based on the mechanics of biological
evolution
• Developed by John Holland, University of Michigan (1970’s)
• To understand the adaptive processes of natural systems
• To design artificial systems software that retains the robustness of natural
systems
,The Genetic Algorithm (cont.)
• Provide efficient, effective techniques for optimization and machine
learning applications
• Widely-used today in business, scientific and engineering circles
, Classes of Search Techniques
Search techniques
Calculus-based techniques Guided random search techniques Enumerative techniques
Direct methods Indirect methods Evolutionary algorithms Simulated annealing Dynamic programming
Finonacci Newton Evolutionary strategies Genetic algorithms
Parallel Sequential
Centralized Distributed Steady-state Generational
