What is a multiobjective optimization problem?
The multiobjective optimization problem (also known as multiobjective programming problem) is a branch of mathematics used in multiple criteria decision-making, which deals with optimization problems involving two or more objective function to be optimized simultaneously.
What is a non dominated solution?
A nondominated solution is one in which no one objective function can be improved without a simultaneous detriment to at least one of the other objectives of the VMP. From: Fundamentals of Optimization Techniques with Algorithms, 2020.
What is multi-objective particle swarm optimization?
Particle swarm optimization (PSO) is a stochastic search method that has been found to be very efficient and effective in solving sophisticated multi-objective problems where conventional optimization tools fail to work well.
What is multiobjective optimization method?
The MOO or the multi-objective optimization refers to finding the optimal solution values of more than one desired goals. The motivation of using the MOO is because in optimization, it does not require complicated equations, which consequently simplifies the problem.
What is the difference between single-objective and multi-objective optimization?
In the single-objective optimization, the superiority of a solution over other solutions was easily determined by comparing their objective function values. However, in the multi-objective optimization problem, the goodness of a solution was determined by the dominance.
How PSO is different from genetic algorithm?
For small scale there is no significant difference between the two methods. Differences are seen in medium and large scale where genetic algorithms can only produce feasible solutions that are near optimal. PSO algorithm has ease of implementation and also has high calculation accuracy.
What is PSO and why is it used?
In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.
Why PSO is faster than GA?
The computational cost of PSO is lower than GA. It means that the number of function evaluation of PSO is much lower than GA. Furthermore, in PSO method, fewer points fall in to local area and more reliable answers are obtained. Pso is faster than GA in terms of convergence.
What is PSO system?
PSO is a stochastic optimization technique based on the movement and intelligence of swarms. In PSO, the concept of social interaction is used for solving a problem. It uses a number of particles (agents) that constitute a swarm moving around in the search space, looking for the best solution.
What is PSO in active directory?
Fine-grained password policies are deployed using password settings objects (PSOs). A PSO contains all the same password settings that exist in all other GPOs. To apply different settings to sets of users, administrators need to create a new PSO and configure the settings as per requirement.
What is meant by PSO?
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