A Comprehensive Survey: Applications of Multi-objective Particle Swarm Optimization (mopso) Algorithm

نویسندگان

  • S. LALWANI
  • Alireza Abdollahi
چکیده

Numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of Multi-Objective Optimization (MOO) had arisen several years ago. Due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by Swarm Intelligence (SI) techniques. Particle Swarm Optimization (PSO) has been established in 1995 and became a very mature and most popular domain in SI. MultiObjective PSO (MOPSO) established in 1999, has become an emerging field for solving MOOs with a large number of extensive literature, software, variants, codes and applications. This paper reviews all the applications of MOPSO in miscellaneous areas followed by the study on MOPSO variants in our next publication. An introduction to the key concepts in MOO is followed by the main body of review containing survey of existing work, organized by application area along with their multiple objectives, variants and further categorized variants.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Review of Multi-objective Particle Swarm Optimization Algorithms in Power System Economic Dispatch

Particle swarm optimization (PSO) has received increasing attention in solving multi-objective economic dispatch (ED) problems in power systems because of parallel computation, faster convergence, and easier implementation. This paper presents a detailed overview of multi-objective particle swarm optimization (MOPSO) and provides a comprehensive survey on its applications in power system econom...

متن کامل

Pareto Optimal Design Of Decoupled Sliding Mode Control Based On A New Multi-Objective Particle Swarm Optimization Algorithm

One of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. In this paper, the decoupled sliding mode control technique (DSMC) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. Furthermore, a new Multi-Objective Particle Swarm O...

متن کامل

Discrete Multi Objective Particle Swarm Optimization Algorithm for FPGA Placement (RESEARCH NOTE)

Placement process is one of the vital stages in physical design. In this stage, modules and elements of circuit are placed in distinct locations according to optimization basis. So that, each placement process tries to influence on one or more optimization factor. In the other hand, it can be told unequivocally that FPGA is one of the most important and applicable devices in our electronic worl...

متن کامل

A Multi-Objective Particle Swarm Optimization Algorithm for a Possibilistic Open Shop Problem to Minimize Weighted Mean Tardiness and Weighted Mean Completion Times

We consider an open shop scheduling problem. At first, a bi-objective possibilistic mixed-integer programming formulation is developed. The inherent uncertainty in processing times and due dates as fuzzy parameters, machine-dependent setup times and removal times are the special features of this model. The considered bi-objectives are to minimize the weighted mean tardiness and weighted mean co...

متن کامل

A Particle Swarm Optimization Based on Multi Objective Functions with Uniform Design

A Multi-objective problems occurs wherever optimal solution necessary to be taken in the presence of tradeoffs between more than one conflicting objectives. Usually the population’s values of MOPSO algorithm are random which leads to random search quality. Particle Swarm Optimization Based on Multi Objective Functions with Uniform Design (MOPSO-UD), is proposed to enhance the accuracy of the pa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013