Which is the best metaheuristic algorithm?
Most widely known Meta-heuristic algorithms are Genetic algorithm (GA), simulated annealing (SA) and Tabu search (TS).
What is a nature inspired algorithm?
Nature-inspired algorithms are a set of novel problem-solving methodologies and approaches derived from natural processes. Some of the popular examples of nature-inspired optimization algorithms include: genetic algorithm, particle swarm optimization, cukcoo search algorithm, ant colony optimization and so on.
What are metaheuristic techniques?
Metaheuristics are strategies that guide the search process. The goal is to efficiently explore the search space in order to find near–optimal solutions. Techniques which constitute metaheuristic algorithms range from simple local search procedures to complex learning processes.
Is PSO heuristic or metaheuristic?
The examples of a metaheuristic method based on population are ACO, GA, and PSO. This research uses three metaheuristic methods, which are ACO, GA, and PSO.
Which algorithm is best for vehicle routing problem?
Metaheuristic algorithms are selected to solve the vehicle routing problem, where GA is implemented as our primary metaheuristic algorithm. GA belongs to the evolutionary algorithm (EA) family, which works on a “survival of the fittest” mechanism.
What is hybrid metaheuristic algorithm?
A metaheuristic algorithm in the combination with other techniques, applied for optimization is known as hybrid metaheuristic algorithms that. may become more effective to handle the real life optimization problems.
What is Spider algorithm?
Social spider algorithm (SSA) is a heuristic algorithm that is created by imitating spiders’ behaviors in nature. SSA is created for organizing searching space of optimization problems as a high-dimensional spider web. In SSA, spiders are SSA agents that perform optimization.
What is Firefly optimization?
Firefly algorithm is one of the new metaheuristic algorithms for optimization problems. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function.
Is genetic algorithm metaheuristic?
In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA).
What is PSO algorithm used for?
In gradient based PSO algorithms, the PSO algorithm is used to explore many local minima and locate a point in the basin of attraction of a deep local minimum. Then efficient gradient based local search algorithms are used to accurately locate the deep local minimum.
What is the difference between TSP and VRP?
TSP considers a single vehicle visiting multiple customer locations before returning to the depot, and we want to minimize the total travel time or vehicle distance. VRP differs from TSP because VRP can generate multiple routes to pass through all customer locations 2 .
Is VRP NP-hard?
The VRP is classified as an NP-hard problem. Hence, the use of exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large.
What is social spider optimization algorithm?
The Social Spider Optimization (SSO) is a novel swarm algorithm that is based on the cooperative characteristics of the social spider. In SSO, search agents represent a set of spiders which collectively move according to the biological behavior of the colony.
Do spiders form colonies?
A social spider is a spider species whose individuals form relatively long-lasting aggregations. Whereas most spiders are solitary and even aggressive toward other members of their own species, some hundreds of species in several families show a tendency to live in groups, often referred to as colonies.
What is fruitfly algorithm?
The Fruit Fly Optimization Algorithm (FOA) is a new method for finding global optimization based on the food finding behavior of the fruit fly. The fruit fly itself is superior to other species in sensing and perception, especially in osphresis and vision, which is as shown in Fig. 1.
Who invented Firefly algorithm?
Xin-She Yang
FA is originally proposed by Xin-She Yang [26, 27], based on the flashing behavior and models of Fireflies. It is renowned that the flash intensity varies with distance from the origin. Fireflies are usual example of the living being which utilizes bioluminescence for sexual selection.
Which approaches used in metaheuristic optimization techniques?
Metaheuristic Optimization Methods developed in recent years can also be considered as metaphor-based optimization methods. All the metaheuristic methods are based on the use of random numbers (probabilistic approaches) in the various stages of the optimization process.
What is the difference between heuristic methods and metaheuristic methods?
Heuristic is a solving method for a special problem (It can benefit from the properties of the solved problem). Metaheuristic is a generalized solving method like GA, TS, etc. Heuristic means “act of discovering”.
What is GREY Wolf algorithm?
The grey wolf optimizer is a novel heuristic swarm intelligent optimization algorithm proposed by Seyedali Mirjalili et al. in 2014. The wolf as top predators in the food chain, has a strong ability to capture prey.
What is the difference between PSO and genetic algorithm?
The results obtained by GA algorithm and those by PSO algorithm are compared. The performance of Particle Swarm Optimization is found to be better than the Genetic Algorithm, as the PSO carries out global search and local searches simultaneously, whereas the Genetic Algorithm concentrates mainly on the global search.
What are nature-inspired algorithms?
This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms.
Can metaheuristics solve NP-hard optimization problems?
Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems.
What are the Most Popular metaheuristics algorithms?
The most popular single-solution-based metaheuristic algorithm is simulated annealing (SA) 14. This algorithm’s process starts with a random candidate solution (a population) and then moves and improves it in the promising search space in an iterative manner to find the superior solution.
Is there an algorithm based on the hunting behavior of Cheetah?
A new bio-inspired algorithm based on the hunting behavior of cheetah. Int. J. Inf. Technol. Project Manag. (IJITPM) 11, 13–30 (2020).