Although significant development of heuristics for various combinatorial optimization problems has been achieved, the extremely expensive computational overhead to tackle large scale problems is still a challenge in its own right. The solution of these problems requires both improvement in mathematical programming algorithms and the utilization of powerful computational platforms. The studies in this dissertation concentrated on memetic algorithms (MAs), a combination of efficient neighborhood search strategies and evolutionary algorithms.DOCTOR OF PHILOSOPHY (EEE
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
© Springer International Publishing AG, part of Springer Nature 2018. All rights reserved. Memetic a...
Although significant development of heuristics for various combinatorial optimization problems has b...
The term memetic algorithms (MAs) was introduced in the late 1980s to denote a family of metaheurist...
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various op...
Memetic algorithms (MAs) constitute a search and optimization paradigm based on the orchestrated int...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
Over the recent years, there has been increasing research activities made on improving the efficacy ...
Memetic Computing (MC) structures are algorithms composed of heterogeneous operators (memes) for sol...
Nature-inspired algorithms are seen as potential tools to solve large-scale global optimization prob...
Parallel Memetic Algorithms (PMAs) are a class of modern parallel meta-heuristics that combine evolu...
In solving practically significant problems of global optimization, the objective function is often ...
To date, most successful advanced stochastic optimization algorithms involve some forms of individua...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
© Springer International Publishing AG, part of Springer Nature 2018. All rights reserved. Memetic a...
Although significant development of heuristics for various combinatorial optimization problems has b...
The term memetic algorithms (MAs) was introduced in the late 1980s to denote a family of metaheurist...
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various op...
Memetic algorithms (MAs) constitute a search and optimization paradigm based on the orchestrated int...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
Over the recent years, there has been increasing research activities made on improving the efficacy ...
Memetic Computing (MC) structures are algorithms composed of heterogeneous operators (memes) for sol...
Nature-inspired algorithms are seen as potential tools to solve large-scale global optimization prob...
Parallel Memetic Algorithms (PMAs) are a class of modern parallel meta-heuristics that combine evolu...
In solving practically significant problems of global optimization, the objective function is often ...
To date, most successful advanced stochastic optimization algorithms involve some forms of individua...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (M...
© Springer International Publishing AG, part of Springer Nature 2018. All rights reserved. Memetic a...