A Novel Discrete Particle Swarm Optimization Algorithm Base on Crossover Operator and Neighborhood Search
نویسندگان
چکیده
منابع مشابه
Particle Swarm Optimization Using Blended Crossover Operator
In recent days, Swarm Intelligence plays an important role in solving many real life optimization problems. Particle Swarm Optimization (PSO) is swarm intelligence based search and optimization algorithm which is used to solve global optimization problems. But due to lack of population diversity and premature convergence it is often trapped into local optima. We can increase diversity and preve...
متن کاملParticle Swarm Optimization Using Crossover Operator
Particle swarm optimization (PSO) has been widely used mainly due to its simple concept and its ability to converge to reasonable solution fast. However, this algorithm is always inefficient while optimizing complex global optimization problems because it is easy to be trapped into local optima. Researches into the combination of evolutionary operators with PSO is one of the most significant an...
متن کاملNovel Mutative Particle Swarm Optimization Algorithm for Discrete Optimization
Mutative Particle Swarm Optimization (MPSO) is swarm-based stochastic optimization algorithm combined with the mutative function inspired by Genetic Algorithm (GA). The algorithm searches for the solution by combining swarming behavior, as well as mutation of the particles to accelerate the search process. This paper presents a modification to the MPSO algorithm for it to solve Integer Programm...
متن کاملVariable Neighborhood Particle Swarm Optimization Algorithm
In this paper, we introduce a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO) algorithm, consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO algorithm is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). Flexible job-shop scheduling is very important in...
متن کاملDiscrete Particle Swarm Optimization for TSP based on Neighborhood
Particle swarm optimization (PSO) is a kind of evolutionary algorithm to find optimal solutions for continuous optimization problems. Updating kinetic equations for particle swarm optimization algorithm are improved to solve traveling salesman problem (TSP) based on problem characteristics and discrete variable. Those strategies which are named heuristic factor, reversion mutant and adaptive no...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Science and Application
سال: 2017
ISSN: 2161-8801,2161-881X
DOI: 10.12677/csa.2017.712141