This paper provides a comprehensive survey of the most popular constraint-handling
techniques currently used with evolutionary algorithms. We review approaches that go from …

Genetic algorithms, and other closely related areas such as genetic programming, evolution
strategies and evolution programs, are the subject of an increasing amount of research …

Energy is a vital resource for human activities and lifestyle, powering important everyday
infrastructures and services. Currently, pollutant and non-renewable sources, such as fossil …

In this paper we present a general genetic algorithm to address a wide variety of sequencing
and optimization problems including multiple machine scheduling, resource allocation, and …

Evolutionary computation techniques have received a great deal of attention regarding their
potential as optimization techniques for complex numerical functions. However, they have …

Artificial Bee Colony (ABC) algorithm was firstly proposed for unconstrained optimization
problems on where that ABC algorithm showed superior performance. This paper describes …

In optimization, multiple objectives and constraints cannot be handled independently of the
underlying optimizer. Requirements such as continuity and differentiability of the cost …

Engineering design problems are generally large scale or nonlinear or constrained
optimization problems. The Artificial Bee Colony (ABC) algorithm is a successful tool for …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

Genetic Algorithms are most directly suited to unconstrained optimization. Application of
Genetic Algorithms to constrained optimization problems is often a challenging effort …