An Introduction To Applied Evolutionary Meta Heuristics
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This presentation introduces some of the main themes in modern evolutionary algorithm research while emphasising their application to problems that exhibit real-world complexity.
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An Introduction To Applied Evolutionary Meta Heuristics
- 3. What is a metaheuristic?
- 9. What is an evolutionary algorithm?
- 15. A general evolutionary algorithm
- 28. Single objective evolutionary algorithms
- 43. What is pareto optimality? [pa-rih-toe]
- 48. Demo #1 The Pareto Front
- 49. Multi-objective evolutionary algorithms Elitism
- 55. Multi-Objective Evolutionary Algorithms Maximise the diversity
- 62. Demo #2 Diversity & Constraints
- 63. What is a constraint?
- 72. Applying an evolutionary algorithm IC-SPEA2
- 77. Applying an evolutionary metaheuristic A beef farm model
- 82. Applying an evolutionary metaheuristic The farm loop
- 88. Applying an evolutionary metaheuristic The farm's objectives
- 96. Applying an evolutionary metaheuristic Discovering counter intuitive solutions
- 103. Applying an evolutionary metaheuristic Implications for farm sustainability
- 113. The End Images courtesy of http://www.goldennumber.net, Gary B. Meisner, Copyright 2006. Fibonacci numbers