Numerically Analyzing Linear Multicriteria Optimization Problems

1988 ◽  
pp. 27-47 ◽  
Author(s):  
Jerald P. Dauer
Keyword(s):  
Multicriteria Optimization ◽  
Optimization Problems

Optimization Problem

2020 ◽  
pp. 276-291
Author(s):  
Albert N. Voronin
Keyword(s):  
Wide Class ◽  
Multicriteria Optimization ◽  
System Approach ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Systemic Approach ◽  
Multicriteria Decision ◽  
Multicriteria Problems ◽  
Linear Scheme ◽  
Non Linear

A systemic approach to solving multicriteria optimization problems is proposed. The system approach allowed uniting the models of individual schemes of compromises into a single integrated structure that adapts to the situation of adopting a multi-criteria solution. The advantage of the concept of non-linear scheme of compromises is the possibility of making a multicriteria decision formally, without the direct participation of a person. The apparatus of the non-linear scheme of compromises, developed as a formalized tool for the study of control systems with conflicting criteria, makes it possible to solve practically multicriteria problems of a wide class.

Definition of the feasible solution set in multicriteria optimization problems with continuous, discrete, and mixed design variables

2009 ◽  
Vol 71 (12) ◽  
pp. e109-e117 ◽  
Author(s):  
Roman Statnikov ◽  
Alex Bordetsky ◽  
Josef Matusov ◽  
Il’ya Sobol’ ◽  
Alexander Statnikov
Keyword(s):  
Multicriteria Optimization ◽  
Feasible Solution ◽  
Optimization Problems ◽  
Solution Set ◽  
Mixed Design ◽  
Design Variables ◽  
Definition Of ◽  
Mixed Design Variables

scholarly journals Solving a multicriteria scheduling problem using a genetic algorithm

2021 ◽  
Vol 5 (1) ◽  
pp. 100-106
Author(s):  
Alina Kazmirchuk ◽  
Olena Zhdanova ◽  
Volodymyr Popenko ◽  
Maiia Sperkach
Keyword(s):  
Genetic Algorithm ◽  
Multicriteria Optimization ◽  
Work Performance ◽  
Optimal Allocation ◽  
Optimization Problems ◽  
Scheduling Problem ◽  
Pareto Solutions ◽  
Advantages And Disadvantages ◽  
Multicriteria Scheduling ◽  
Multiobjective Optimization Problems

The work is devoted to the multiobjective task of scheduling, in which a given set of works must be performed by several performers of different productivity. A certain number of bonuses is accrued for the work performed by the respective executor, which depends on the time of work performance. The criteria for evaluating the schedule are the total time of all jobs and the amount of bonuses spent. In the research the main approaches to solving multiobjective optimization problems were analyzed, based on which the Pareto approach was chosen. The genetic algorithm was chosen as the algorithm. The purpose of this work is to increase the efficiency of solving multicriteria optimization problems by implementing a heuristic algorithm and increase its speed. The tasks of the work are to determine the advantages and disadvantages of the approaches used to solve multicriteria optimization problems, to develop a genetic algorithm for solving the multicriteria scheduling problem and to study its efficiency. Operators of the genetic algorithm have been developed, which take into account the peculiarities of the researched problem and allow to obtain Pareto solutions in the process of work. Due to the introduction of parallel calculations in the implementation of the genetic algorithm, it was possible to increase its speed compared to the conventional version. The developed algorithm can be used in solving the problem of optimal allocation of resources, which is part of the system of accrual of bonuses to employees.

Sign in / Sign up

Export Citation Format

Share Document