<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

Institute of Information and Communication Technologies

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The paper presents a hybrid metaheuristic algorithm, including a Particle Swarm Optimization (PSO) procedure and elements of Tabu Search (TS) metaheuristic....

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

Pubblicato online: 11 dic 2019

Pagine: 26 - 44

Ricevuto: 07 ago 2019

Accettato: 01 nov 2019

DOI: https://doi.org/10.2478/cait-2019-0034

Parole chiave
Flexible Job Shop Scheduling Problem (FJSSP), Particle Swarm Optimization (PSO), Tabu Search (TS)

© 2018 Asen Toshev, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Pubblicato online: 11 dic 2019

Pagine: 26 - 44

Ricevuto: 07 ago 2019

Accettato: 01 nov 2019

DOI: https://doi.org/10.2478/cait-2019-0034

Parole chiaveFlexible Job Shop Scheduling Problem (FJSSP), Particle Swarm Optimization (PSO), Tabu Search (TS)

© 2018 Asen Toshev, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Flexible Job Shop Scheduling Problem (FJSSP), Particle Swarm Optimization (PSO), Tabu Search (TS)