Differential Evolution: A review of more than two decades of research
Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …
frequently used algorithms for solving complex optimization problems. Its flexibility and …
Multi-objective optimization techniques: a survey of the state-of-the-art and applications: Multi-objective optimization techniques
In recent years, multi-objective optimization (MOO) techniques have become popular due to
their potentiality in solving a wide variety of real-world problems, including bioinformatics …
their potentiality in solving a wide variety of real-world problems, including bioinformatics …
A survey on evolutionary constrained multiobjective optimization
Handling constrained multiobjective optimization problems (CMOPs) is extremely
challenging, since multiple conflicting objectives subject to various constraints require to be …
challenging, since multiple conflicting objectives subject to various constraints require to be …
A survey on evolutionary computation for complex continuous optimization
Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …
development of the economy and society. Moreover, the technologies like Internet of things …
An enhanced MSIQDE algorithm with novel multiple strategies for global optimization problems
Quantum-inspired differential evolution (QDE) is an evolutionary algorithm, which can
effectively solve complex optimization problems. However, sometimes, it easily leads to …
effectively solve complex optimization problems. However, sometimes, it easily leads to …
A test-suite of non-convex constrained optimization problems from the real-world and some baseline results
Real-world optimization problems have been comparatively difficult to solve due to the
complex nature of the objective function with a substantial number of constraints. To deal …
complex nature of the objective function with a substantial number of constraints. To deal …
Improved multi-operator differential evolution algorithm for solving unconstrained problems
In recent years, several multi-method and multi-operator-based algorithms have been
proposed for solving optimization problems. Generally, their performance is better than other …
proposed for solving optimization problems. Generally, their performance is better than other …
Dynamic auxiliary task-based evolutionary multitasking for constrained multiobjective optimization
When solving constrained multiobjective optimization problems (CMOPs), the utilization of
infeasible solutions significantly affects algorithm's performance because they not only …
infeasible solutions significantly affects algorithm's performance because they not only …
Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces
Constrained multiobjective optimization problems (CMOPs) are frequently encountered in
real-world applications, which usually involve constraints in both the decision and objective …
real-world applications, which usually involve constraints in both the decision and objective …
An adaptive regeneration framework based on search space adjustment for differential evolution
Differential evolution (DE) is a well-known evolutionary algorithm with simple operation and
excellent performance, which has been applied to solve various optimization problems. To …
excellent performance, which has been applied to solve various optimization problems. To …