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...

in this article, multiple-product pvrp with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. a mathematical formulation was provided for this problem. each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. to solve the problem, two meta-heuristic methods...

This paper introduces a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO), consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO method is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). The details of implementation for the multi-objective FJSP and the c...

Abstract There are many complex multi-objective optimization problems in the real world, which difficult to solve using traditional methods. Multi-objective particle swarm is one of effective algorithms such problems. This paper proposes a with dynamic population size (D-MOPSO), helps compensate for lack convergence and diversity brought by optimization, makes full use existing resources search...

In this paper multi objective optimization problem for partitioning process of VLSI circuit optimization is solved using IPO algorithm. The methodology used in this paper is based upon the dynamic of sliding motion along a frictionless inclined plane. In this work, modules and elements of the circuit are divided into two smaller parts (components) in order to minimize the cutsize and area imbal...

The selection of global best (Gbest) exerts a high influence on the searching performance multi-objective particle swarm optimization algorithm (MOPSO). candidates MOPSO in external archive are always estimated to select Gbest. However, most estimation methods, considered as Gbest fixed way, which is difficult adapt varying evolutionary requirements for balance between convergence and diversity...

As the computer technology improves rapidly, the scale of software has increased greatly, which makes it more and more difficult to find a bug in software. As a result, the enhancement of software quality and reliability has become an important task in the field of software engineering. Test is an important step that guarantees software quality and reliability. We put forward a novel multi-obje...

A distributed variant of multi-objective particle swarm optimization called multi-objective parallel asynchronous particle swarm optimization (MOPAPSO) was used to develop a new optimization-based synthesis routine for Grashof mechanisms. By using a formal multi-objective handling scheme based on Pareto dominance criteria, the need to pre-weight competing objective functions is removed and the ...