Showing papers on "Multi-objective optimization published in 1975"

Approach to performance and sensitivity multiobjective optimization: The goal attainment method

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.

Directions in Large-Scale Systems. Many-Person Optimization and Decentralized Control. Proceedings of a Symposium Held at Wakefield, Massachusetts on 1-3 September 1975,

Abstract: : Contents: Information Flow in Decentralized Systems; Decentralized Control and Large Scale Systems; Comparison of Information Structures in Decentralized Dynamic Systems; On Fluctuations in Microscopic States of a Large System; Flow Systems; Some Remarks on the Concept of State; On Multicriteria Optimization; Dynamic Games with Coalitions and Diplomacies; Three Methods for Determining Pareto-Optimal Solutions of Multiple-Objective Problems; Stackelberg Strategies for Multilevel Systems; Incentive Compatible Control of Decentralized Organizations; Some Thoughts About Simple Advertising Models as Differential Games and the Structure of Coalitions; Equilibrium Patterns for Bargaining under Stirke:A Differential Game Model; Permanent Differential Games: Quasi Stationary and Relaxed Steady-State Operations; Modelling and Control of the U.K. Economy; Decentralized Management and Optimization of Development; Organization and Control; Decentralized Stabilization and Regulation in Large Multivariable Systems; The Role of Poles and Zeros in Multivariable Feedback Theory; The Linguistic Approach and Its Application to Decision Analysis; Fuzzy Core and Equilibria of Games Defined in Strategic Form; Stabilization and Optimal Control of Nonlinear Systems Homogeneous-in-the-Input; Stability of Large Scale Interconnected Systems; Large-Scale Systems: Optimality vs. Reliability.

Multiple-objective optimization for environment development systems

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...

Selection of optimal parameters for multipurpose controllable systems: General formulation of the problem and solution algorithms

Abstract: This paper describes an approach to the selection of optimal parameters for multipurpose controllable systems intended to perform a series of maneuvers. The paper is an extension of the writer's previous papers on the subject (Refs. 1---6). It states the problem in general terms and discusses the selection of a functional. Depending on the amount of available data on the parameters of maneuver, the problem reduces to either minimization of a function of many variables or a game problem. Algorithms for the solution of the problems formulated are developed. A model problem of space flight mechanics with low-thrust engines is used for illustration purposes. Several applications of the approach developed are contained in Refs. 7---9. In addition, Refs. 8---9 suggest one more method for solving the problem of Section 3, the so-called method of optimal coverings. Another direction of research is described in Ref. 10.