Many design problems in engineering have highly nonlinear constraints and the proper handling of such constraints can be important to ensure solution quality. There are many different ways of handling constraints and different algorithms for optimization problems, which makes it difficult to choose for users. This paper compares six different constraint-handling techniques such as penalty methods, barrier functions, epsilon-constrained method, feasibility criteria and stochastic ranking. The pressure vessel design problem is solved by the flower pollination algorithm, and results show that stochastic ranking and epsilon-constrained method are most effective for this type of design optimization
Almost all real-world and engineering problems involve multi-objective optimization of some sort tha...
Engineering design problems are most frequently charac-terized by constraints that make them hard to...
The flower pollination algorithm (FPA) is a highly efficient metaheuristic optimization algorithm th...
Many design problems in engineering have highly nonlinear constraints and the proper handling of suc...
Optimization methods play an indispensable role in today’s competitive environmentand there are plen...
In engineering design, optimization is customary, and often indispensable. Typical cases include min...
This paper presents a population-based evolutionary computation model for solving continuous constra...
This paper presents a population-based evolutionary computation model for solving continuous constra...
Metaheuristic algorithms are proven to be more effective on finding global optimum in numerous probl...
Metaheuristic algorithms are proven to be more effective on finding global optimum in numerous probl...
Optimization is the process of finding the best solution from a set of available solutions of a prob...
Real-world engineering design optimization problems involve constraints that must be satisfied for t...
Over the years, several meta-heuristic algorithms were proposed and are now emerging as common metho...
Firefly-Algorithm (FA) is an eminent nature-inspired swarm-based technique for solving numerous real...
Metaheuristic optimization algorithms (Nature-Inspired Optimization Algorithms) are a class of algor...
Almost all real-world and engineering problems involve multi-objective optimization of some sort tha...
Engineering design problems are most frequently charac-terized by constraints that make them hard to...
The flower pollination algorithm (FPA) is a highly efficient metaheuristic optimization algorithm th...
Many design problems in engineering have highly nonlinear constraints and the proper handling of suc...
Optimization methods play an indispensable role in today’s competitive environmentand there are plen...
In engineering design, optimization is customary, and often indispensable. Typical cases include min...
This paper presents a population-based evolutionary computation model for solving continuous constra...
This paper presents a population-based evolutionary computation model for solving continuous constra...
Metaheuristic algorithms are proven to be more effective on finding global optimum in numerous probl...
Metaheuristic algorithms are proven to be more effective on finding global optimum in numerous probl...
Optimization is the process of finding the best solution from a set of available solutions of a prob...
Real-world engineering design optimization problems involve constraints that must be satisfied for t...
Over the years, several meta-heuristic algorithms were proposed and are now emerging as common metho...
Firefly-Algorithm (FA) is an eminent nature-inspired swarm-based technique for solving numerous real...
Metaheuristic optimization algorithms (Nature-Inspired Optimization Algorithms) are a class of algor...
Almost all real-world and engineering problems involve multi-objective optimization of some sort tha...
Engineering design problems are most frequently charac-terized by constraints that make them hard to...
The flower pollination algorithm (FPA) is a highly efficient metaheuristic optimization algorithm th...