Work partially supported by FCT grant POCTI/MAT/58957/2004.In this work we consider the problem of finding all the global maximizers of a given multimodal optimization problem. We propose a new algorithm that combines the simulated annealing (SA) method with a function stretching technique to generate a sequence of global maximization problems that are defined whenever a new maximizer is identified. Each global maximizer is located through a variant of the SA algorithm. Results of numerical experiments with a set of well-known test problems show that the proposed method is effective. We also compare the performance of our algorithm with other multi-global optimizers
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Simulated annealing is a global optimization method that distinguishes between different local optim...
Semi-infinite programming (SIP) problems are characterized by a finite number of variables and an in...
In this work we consider the problem of finding all the global maximizers of a given nonlinear optim...
In this work we consider the problem of finding all the global maximizers of a given nonlinear optim...
In this work we consider the problem of finding all the global maximizers of a given nonlinear optim...
Particle swarm and simulated annealing optimization algorithms proved to be valid in finding a globa...
In this talk we consider the problem of finding all the global solutions of a nonlinear optimization...
This paper presents a new simulated annealing algorithm to solve constrained multi-global optimizat...
We consider the problem of finding all the global (and some local) minimizers of a given nonlinear o...
In a multiglobal optimization problem we aim to find all the global solutions of a constrained nonli...
Particle swarm and simulated annealing optimization algorithms proved to be valid in finding a globa...
In a multiglobal optimization problem we aim to find all the global solutions of a constrained nonli...
Stretched Simulated Annealing (SSA) combines simulated annealing with a stretching function techniqu...
In this paper we are concerned with global optimization, which can be defined as the problem of find...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Simulated annealing is a global optimization method that distinguishes between different local optim...
Semi-infinite programming (SIP) problems are characterized by a finite number of variables and an in...
In this work we consider the problem of finding all the global maximizers of a given nonlinear optim...
In this work we consider the problem of finding all the global maximizers of a given nonlinear optim...
In this work we consider the problem of finding all the global maximizers of a given nonlinear optim...
Particle swarm and simulated annealing optimization algorithms proved to be valid in finding a globa...
In this talk we consider the problem of finding all the global solutions of a nonlinear optimization...
This paper presents a new simulated annealing algorithm to solve constrained multi-global optimizat...
We consider the problem of finding all the global (and some local) minimizers of a given nonlinear o...
In a multiglobal optimization problem we aim to find all the global solutions of a constrained nonli...
Particle swarm and simulated annealing optimization algorithms proved to be valid in finding a globa...
In a multiglobal optimization problem we aim to find all the global solutions of a constrained nonli...
Stretched Simulated Annealing (SSA) combines simulated annealing with a stretching function techniqu...
In this paper we are concerned with global optimization, which can be defined as the problem of find...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Simulated annealing is a global optimization method that distinguishes between different local optim...
Semi-infinite programming (SIP) problems are characterized by a finite number of variables and an in...