A Particle Swarm Optimization Approach to Joint Location and Scheduling Decisions in A Flexible Job Shop Environment

Hybrid Particle Swarm Optimization with Genetic Operators and Cauchy Distribution for Flexible Job-shop Scheduling Problem

Flexible job-shop scheduling problem (FJSP) has been well known as one of the most difficult NP-hard combinatorial optimization problems. This problem FJSP is an extension of job-shop scheduling problem (JSP) which is to create a sequence of operations satisfying the precedence relationship together with assignment of time and resources for each operation. Thus, the FJSP model is closer to the ...

An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem

Particle Swarm Optimization Based Parameter Identification Applied to a Target Tracker Robot with Flexible Joint

This paper focuses on parameter identification of a target tracker robot possessing flexible joints using particle swarm optimization (PSO) algorithm. Since, belt and pulley mechanisms are known as flexible joints in robotic systems, their elastic behavior affecting a tracker robot is investigated in this work. First, dynamic equations governing the robot behavior are extracted taking into acco...

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) ...

A Discrete Particle Swarm Optimization Approach for Grid Job Scheduling

Scheduling is one of the core steps to efficiently exploit the capabilities of emergent computational systems such as grid. Grid environment is a dynamic, heterogeneous and unpredictable one sharing different services among many different users. Because of heterogeneous and dynamic nature of grid, the methods used in traditional systems could not be applied to grid scheduling and therefore new ...

Variable Neighborhood Particle Swarm Optimization for Multi-objective Flexible Job-Shop Scheduling Problems

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...