CS2004_Evolutionary_Algorithms_Flashcards
(14 cards)
What is a Genetic Algorithm (GA)?
A GA is a population-based optimisation algorithm inspired by natural selection, using crossover, mutation, and selection to evolve solutions.
What is a chromosome in GA?
A chromosome is a candidate solution encoded as a string (e.g. binary or list of values).
What is crossover in GA?
Crossover combines two parent chromosomes to produce offspring, encouraging recombination of good traits.
✅ Example: One-point, two-point, or uniform crossover.
What is mutation in GA?
Mutation randomly alters parts of a chromosome to maintain genetic diversity.
✅ Example: Flipping a bit in a binary string.
What is fitness proportionate selection (roulette wheel)?
A selection method where the chance of selection is proportional to a chromosome’s fitness score.
What is Genetic Programming (GP)?
GP is an evolutionary algorithm that evolves programs or symbolic expressions, typically represented as syntax trees.
What operators are used in Genetic Programming?
Tree-based crossover and mutation are used to evolve the structure and content of programs.
What is Evolutionary Programming (EP)?
EP focuses on evolving solution parameters using mutation and tournament selection, without using crossover.
What is Particle Swarm Optimisation (PSO)?
PSO is a population-based optimisation method where each solution is a particle moving through the search space influenced by personal and global bests.
What is Ant Colony Optimisation (ACO)?
ACO is a search technique inspired by ant foraging, using pheromone trails and probabilistic decisions to build good solutions over time.
What is stigmergy in ACO?
Stigmergy is indirect communication via the environment — ants lay pheromones to influence other ants’ decisions.
What is pBest and gBest in PSO?
pBest is the best position found by the particle; gBest is the best found by any particle in the swarm.
What is the role of pheromone evaporation in ACO?
It reduces the influence of older paths over time, allowing exploration of new paths.
What is the main difference between GA and EP?
GA uses crossover and selection on chromosomes, while EP uses mutation and tournament selection on real-valued individuals.
