Showing papers on "Multi-swarm optimization published in 1975"
TL;DR: A new computational method is presented, the goal attainment method, which overcomes some of the limitations and disadvantages of methods currently available and presents an integrated, multiobjective treatment of performance and sensitivity optimization based on a vector index approach.
Abstract: This short paper is concerned with computational methods for solving optimization problems with a vector-valued index function (vector optimization). It uses vector optimization as a tool for analyzing static control problems with performance and parameter sensitivity indices. The first part of this short paper presents a new computational method, the goal attainment method, which overcomes some of the limitations and disadvantages of methods currently available. The second part presents an integrated, multiobjective treatment of performance and sensitivity optimization based on a vector index approach. A numerical example in electric power system control is included, with analysis and results demonstrating the use of the goal attainment method and application of the approach to performance and sensitivity optimization.
234 citations
TL;DR: Some recent work by the author on nonlinear minimax optimization is used to derive an efficient algorithm for the minimax optimized problem and the algorithm is applied to the problem of choosing the coefficients of a recursive digital filter to meet arbitrary design specifications on the magnitude or the group delay characteristics.
Abstract: The purpose of this paper is to use some recent work by the author on nonlinear minimax optimization to derive an efficient algorithm for the minimax optimization problem. This is followed by the application of the algorithm to the problem of choosing the coefficients of a recursive digital filter to meet arbitrary design specifications on the magnitude or the group delay characteristics.
25 citations
TL;DR: The problem of multiple-objective optimization for the environment development system is formulated and the so-called Pareto-optimal solution set is formulated, related in a one-to-one manner to a family of auxiliary scalar index problems.
Abstract: This paper deals with multiple-objective optimization problems for the environment development system. The model of the environment development system, which was introduced by Kulikowski, is described by a system of non linear differential equations which include interconnected n exogenous and m endogenous controlled factors or processes. The problem of multiple-objective optimization for the environment development system is formulated. A main difficulty of multiple-objective optimization is that it is no longer clear what one means by an optimal solution. A possible remedy for this situation is to refine the concept of optimal solution by introducing the so-called Pareto-optimal solution set. Then multiple-objective optimization problem boils down to determining the set of Pareto-optimal solutions. The Pareto-optimal solution set is related in a one-to-one manner to a family of auxiliary scalar index problems. For an unconstrained multiple-objective optimization problem for the environment deve...
7 citations
TL;DR: A new algorithm for solving constrained optimization problems, based on a method proposed by Chattopadhyay, is described, which replaces the original problem withm constraints,m>1, by a sequence of optimization problems with one constraint.
Abstract: This paper describes a new algorithm for solving constrained optimization problems, based on a method proposed by Chattopadhyay. The proposed algorithm replaces the original problem withm constraints,m>1, by a sequence of optimization problems, with one constraint. Here, we modify the algorithm given by Chattopadhyay in order to make it applicable for a larger class of optimization problems and to improve its convergence characteristics.
1 citations
TL;DR: This suite provides an interactive automated design aid within a small-machine environment and a unified approach for time-domain design is presented, based on the development of the adjoint-network from Tellegen's theorem.
Abstract: A program suite for the optimization of nonlinear networks is described. This suite provides an interactive automated design aid within a small-machine environment. A unified approach for time-domain design is presented. A generalized form of performance function is used and is based on the development of the adjoint-network from Tellegen's theorem. A suitable set of the adjoint-network excitations is also obtained. The constrained optimization of the performance function is transformed by a change of variables into an unconstrained problem. Powell's algorithm for unconstrained minimization is used. The optimization algorithm requires the value of the performance function and its derivatives which are obtained from analyses of the network and its adjoint. The program is implemented on a small computer with 16k words of (16-bit) core store. The overall structure of the program suite is described and results of the optimization of some simple circuits are given.