What is Multi-Objective Optimization

1.

In the world around us it is rare for any problem to concern only a single value or objective. Generally, multiple objectives or parameters have to be met or optimized before any ‘master’ or ‘holistic’ solution is considered adequate. Most realistic optimization problems, particularly those in design, require the simultaneous optimization of more than one objective function. Learn more in: Simulation Model of Ant Colony Optimization for the FJSSP

2.

Multi-objective optimization is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Learn more in: Combined Electromagnetism-Like Algorithm with Tabu Search to Scheduling

3.

A topic of multiple-criteria decision-making dealing with mathematical optimization problems which consists of more than one objective to be optimized at the same time. Learn more in: An Integrated Methodology for Order Release and Scheduling in Hybrid Manufacturing Systems: Considering Worker Assignment and Utility Workers

4.

Optimization of a problem that involves the satisfacibility or optimization of two or more objectives, sometimes opposed each other. Learn more in: Multi-Objective Training of Neural Networks

5.

Also recognized as multi criteria optimization or multi attribute optimization, is an arena of multiple criteria decision making, which is concerned with mathematical optimization problems entailing more than one objective function to be optimized simultaneously. Learn more in: Application of Standard Deviation Method Integrated PSO Approach in Optimization of Manufacturing Process Parameters

6.

A mathematical method that aims to find the optimal solution for problems involving multiple objectives. Learn more in: The Effect of Product Modularity on Supplier Integration: A Multi-Objective Approach

7.

It deals with decision making for problems that require simultaneous optimization of several non-commensurable and often competitive/conflicting objectives. Learn more in: Swarm Intelligence for Multi-Objective Optimization in Engineering Design

8.

An optimization problem involving more than a single objective function. Learn more in: Improving Energy Efficiency in Industry 4.0 With Multi-Objective Optimization

9.

Multi-objective optimization involves more than one objective function to be optimized simultaneously. The task is more challenging as it results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Learn more in: From Optimization to Clustering: A Swarm Intelligence Approach

10.

Decision making for problems that require simultaneous optimization of several non-commensurable and often competitive/conflicting objectives. Learn more in: Elitist-Mutated Multi-Objective Particle Swarm Optimization for Engineering Design

11.

An optimization problem involving more than a single objective function. In such a setting, it is not easy to discriminate between good and bad solutions, as a solution, which is better than another in one objective, may be poorer in another. Without any loss of generality, any optimization problem can be cast as one involving minimizations only Learn more in: Multi-Objective Evolutionary Algorithms

12.

A sub area of multiple criteria decision making dealing with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Learn more in: Fuzzy Multi-Objective Association Rule Mining Using Evolutionary Computation

13.

Method to find out a set of representative Pareto optimal solutions and quantify the trade-offs in satisfying the different multiple objectives. Learn more in: Cancer Biomarker Assessment Using Evolutionary Rough Multi-Objective Optimization Algorithm

14.

It deals with decision making for problems that require simultaneous optimization of several non-commensurable and often competitive/conflicting objectives. Learn more in: Multiobjective Optimization in Water and Environmental Systems Management- MODE Approach

15.

Mathematical optimization problems involving more than one objective function to be optimized simultaneously. Learn more in: Guaranteeing User Rates With Reinforcement Learning in 5G Radio Access Networks

16.

is the process of simultaneously optimizing two or more conflicting objectives subject to certain number of constraints. Learn more in: Competency Mapping in Academic Environment: A Swarm Intelligence Approach

17.

Optimization of mathematical models that share the same decision variables but differ in their objectives and constraints. Learn more in: Strategic Decision Making in Global Supply Networks

18.

optimization problem involving more than one objective function to be optimized simultaneously. Learn more in: Supply Chain Network Design Using an Enhanced Hybrid Swarm-Based Optimization Algorithm

19.

Mathematical optimization problems involving more than one objective function to be optimized simultaneously. Learn more in: Machine Learning in Radio Resource Scheduling

20.

An optimization problem involving more than a single objective function. In such a setting, it is not easy to discriminate between good and bad solutions, as a solution that is better than another in one objective may be poorer in another. Without any loss of generality, each objective function can be considered to be one involving maximization. Learn more in: Nelder-Mead Evolutionary Hybrid Algorithms

21.

A topic of multiple-criteria decision-making dealing with mathematical optimization problems which consists of more than one objective to be optimized at the same time. Learn more in: Evolutionary Algorithms for Multi-Objective Scheduling in a Hybrid Manufacturing System

22.

Optimization problems arrive at a solution that best satisfies a goal. Multiple such goals need to be simultaneously satisfied for the class of Multi-Objective Optimization problems. Learn more in: An Investigation on Quality Perspective of Software Functional Artifacts

23.

It is the method to optimize variable objective functions simultaneously. Learn more in: Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey

24.

Optimization problem involving more than one objective function to be optimized simultaneously. Learn more in: The Bees Algorithm and Its Applications