Clever Algorithms: Nature-Inspired Programming Recipes

By J. Brownlee. 2012

688 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Metaheuristic design of feedforward neural networks: A review of two decades of research (2017, unknown): “Under the definition of memetic algorithms, researchers combine EAs with conventional algorithms [126].”
Chaotic grasshopper optimization algorithm for global optimization (2019, methodology): “Many heuristic algorithms are being used in optimization area; for example, Bat Swarm Optimization (BSO) [5], Hill Climbing (HC) [6] and Simulated Annealing (SA) [2, 7].”
A survey on optimization metaheuristics (2013, background): “Stützle does not take credit for the approach, and instead highlights specific instances of ILS from the literature, such as iterated descent [20], large-step Markov chains [176], iterated Lin-Kernigha n [139], chained local optimization [175], as well as [21] that introduces the principle, and [140”
A survey on nature inspired metaheuristic algorithms for partitional clustering (2014, background): “Literature review [44,45] reveals the recent trend to name all stochastic algorithms with randomization and local search as ‘metaheuristic’.”
Towards interactive Machine Learning (iML): Applying Ant Colony Algorithms to Solve the Traveling Salesman Problem with the Human-in-the-Loop Approach (2016, unknown): “The evolution in this case is a probabilistic stepwise construction of a path, making use of pheromones and problem-specific heuristic information to incrementally find a solution [34,35].”