Based on Tabu Search and Particle Swarm Optimization Algorithms Solving Job Shop Scheduling Optimization Problems

2013 ◽  
Author(s):  
Liang Xu ◽  
Li Yanpeng ◽  
Jiao Xuan
Keyword(s):  
Particle Swarm Optimization ◽  
Tabu Search ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Particle Swarm ◽  
Scheduling Optimization ◽  
Swarm Optimization ◽  
Shop Scheduling

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.

A PARTICLE SWARM OPTIMIZATION-BASED ALGORITHM FOR JOB-SHOP SCHEDULING PROBLEMS

2005 ◽  
Vol 02 (03) ◽  
pp. 419-430 ◽  
Author(s):  
H. W. GE ◽  
Y. C. LIANG ◽  
Y. ZHOU ◽  
X. C. GUO
Keyword(s):  
Particle Swarm Optimization ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Particle Swarm ◽  
Traditional Scheduling ◽  
Benchmark Problems ◽  
Scheduling Problems ◽  
Swarm Optimization ◽  
Shop Scheduling ◽  
Novel Concept

A novel particle swarm optimization (PSO)-based algorithm is developed for job-shop scheduling problems (JSSP), which are the most general and difficult issues in traditional scheduling problems. Our goal is to develop an efficient algorithm based on swarm intelligence for the JSSP. Thereafter a novel concept for the distance and velocity of particles in the PSO is proposed and introduced to pave the way for the JSSP. The proposed algorithm effectively exploits the capabilities of distributed and parallel computing systems, with simulation results showing the possibilities of high quality solutions for typical benchmark problems.

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