An Approximation Algorithm for Diagnostic Test Scheduling in Multicomputer Systems
IEEE Transactions on Computers
Scheduling Multiprocessor Tasks to Minimize Schedule Length
IEEE Transactions on Computers
Complexity of scheduling parallel task systems
SIAM Journal on Discrete Mathematics
Scheduling independent two processor tasks on a uniform duo-processor system
Discrete Applied Mathematics - Combinatorial Optimization
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Scheduling multiprocessor tasks in a two-stage flow-shop environment
Proceedings of the 21st international conference on Computers and industrial engineering
Scheduling Computer and Manufacturing Processes
Scheduling Computer and Manufacturing Processes
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Improved genetic algorithm for the permutation flowshop scheduling problem
Computers and Operations Research
Heuristic algorithms for the two-stage hybrid flowshop problem
Operations Research Letters
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Proportionate flexible flow shop scheduling via a hybrid constructive genetic algorithm
Expert Systems with Applications: An International Journal
A performance comparison of PSO and GA in scheduling hybrid flow-shops with multiprocessor tasks
Proceedings of the 2008 ACM symposium on Applied computing
Expert Systems with Applications: An International Journal
Robotics and Computer-Integrated Manufacturing
A genetic algorithm-based approach for solving the resource-sharing and scheduling problem
Computers and Industrial Engineering
Performance of local search heuristics on scheduling a class of pipelined multiprocessor tasks
Computers and Electrical Engineering
Computers and Operations Research
Application of EM algorithm to hybrid flow shop scheduling problems with a special blocking
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
The production scheduling problem in a multi-page invoice printing system
Computers and Operations Research
Performance of particle swarm optimization in scheduling hybrid flow-shops with multiprocessor tasks
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
Quantum genetic algorithm for hybrid flow shop scheduling problems to minimize total completion time
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II
Non-identical parallel machine scheduling using genetic algorithm
Expert Systems with Applications: An International Journal
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Heuristic algorithms for assigning and scheduling flight missions in a military aviation unit
Computers and Industrial Engineering
A genetic algorithm for two-stage no-wait hybrid flow shop scheduling problem
Computers and Operations Research
Computers and Operations Research
Computers and Operations Research
Improved bounds for hybrid flow shop scheduling with multiprocessor tasks
Computers and Industrial Engineering
The optimal number of used machines in a two-stage flexible flowshop scheduling problem
Journal of Scheduling
| Hi-index | 0.00 |
The hybrid flow-shop scheduling problem with multiprocessor tasks finds its applications in real-time machine-vision systems among others. Motivated by this application and the computational complexity of the problem, we propose a genetic algorithm in this paper. We first describe the implementation details, which include a new crossover operator. We then perform a preliminary test to set the best values of the control parameters, namely the population size, crossover rate and mutation rate. Next, given these values, we carry out an extensive computational experiment to evaluate the performance of four versions of the proposed genetic algorithm in terms of the percentage deviation of the solution from the lower bound value. The results of the experiments demonstrate that the genetic algorithm performs the best when the new crossover operator is used along with the insertion mutation. This genetic algorithm also outperforms the tabu search algorithm proposed in the literature for the same problem.