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

2006 ◽  
pp. 197-204 ◽  
Author(s):  
Hongbo Liu ◽  
Ajith Abraham ◽  
Okkyung Choi ◽  
Seong Hwan Moon
Keyword(s):  
Particle Swarm Optimization ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Particle Swarm ◽  
Flexible Job Shop ◽  
Scheduling Problems ◽  
Flexible Job Shop Scheduling ◽  
Swarm Optimization ◽  
Shop Scheduling ◽  
Multi Objective

scholarly journals Particle Swarm Optimization and Tabu Search Hybrid Algorithm for Flexible Job Shop Scheduling Problem – Analysis of Test Results

2019 ◽  
Vol 19 (4) ◽  
pp. 26-44
Author(s):  
Asen Toshev
Keyword(s):  
Particle Swarm Optimization ◽  
Tabu Search ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Particle Swarm ◽  
Flexible Job Shop ◽  
Test Results ◽  
Flexible Job Shop Scheduling ◽  
Swarm Optimization ◽  
Shop Scheduling

Abstract The paper presents a hybrid metaheuristic algorithm, including a Particle Swarm Optimization (PSO) procedure and elements of Tabu Search (TS) metaheuristic. The novel algorithm is designed to solve Flexible Job Shop Scheduling Problems (FJSSP). Twelve benchmark test examples from different reference sources are experimentaly tested to demonstrate the performance of the algorithm. The obtained mean error for the deviation from optimality is 0.044%. The obtained test results are compared to the results in the reference sources and to the results by a genetic algorithm. The comparison illustrates the good performance of the proposed algorithm. Investigations on the base of test examples with a larger dimension will be carried out with the aim of further improvement of the algorithm and the quality of the test results.

Sign in / Sign up

Export Citation Format

Share Document