Heuristics for scheduling flexible flow lines
Computers and Industrial Engineering
Hybrid flow shop scheduling: a survey
Computers and Industrial Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Searching for Memory in Artificial Immune System
Proceedings of the IIS'2002 Symposium on Intelligent Information Systems
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Improving Artificial Immune System Performance: Inductive Bias and Alternative Mutations
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Automatic knot adjustment using an artificial immune system for B-spline curve approximation
Information Sciences: an International Journal
A multi-modal immune algorithm for the job-shop scheduling problem
Information Sciences: an International Journal
A variable neighborhood search for job shop scheduling with set-up times to minimize makespan
Future Generation Computer Systems
An Artificial Immune System for the Multi-Mode Resource-Constrained Project Scheduling Problem
EvoCOP '09 Proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization
Computers and Industrial Engineering
Watermarking schema using an artificial immune system in spatial domain
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
A hybrid immune-estimation distribution of algorithm for mining thyroid gland data
Expert Systems with Applications: An International Journal
Computers and Operations Research
An artificial immune algorithm for the flexible job-shop scheduling problem
Future Generation Computer Systems
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
Investigating a hybrid metaheuristic for job shop rescheduling
ACAL'07 Proceedings of the 3rd Australian conference on Progress in artificial life
Incorporating periodic preventive maintenance into flexible flowshop scheduling problems
Applied Soft Computing
Expert Systems with Applications: An International Journal
A review of clonal selection algorithm and its applications
Artificial Intelligence Review
An artificial immune system based algorithm to solve unequal area facility layout problem
Expert Systems with Applications: An International Journal
A simple artificial immune system (SAIS) for generating classifier systems
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Application of immune algorithms on solving minimum-cost problem of water distribution network
Mathematical and Computer Modelling: An International Journal
A two-stage hybrid flowshop scheduling problem in machine breakdown condition
Journal of Intelligent Manufacturing
An Ant Colony System Algorithm for the Hybrid Flow-Shop Scheduling Problem
International Journal of Applied Metaheuristic Computing
Computers and Industrial Engineering
Computers and Operations Research
Computers and Industrial Engineering
Computers and Operations Research
Binary Accelerated Particle Swarm Algorithm (BAPSA) for discrete optimization problems
Journal of Global Optimization
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Artificial immune system (AIS) is an intelligent problem-solving technique that has been used in scheduling problems for about 10 years. AIS are computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. In this research, a computational method based on clonal selection principle and affinity maturation mechanism of the immune response is used. The n-job, k-stage hybrid flow shop problem is one of the general production scheduling problems. Hybrid flow shop (HFS) problems are NP-Hard when the objective is to minimize the makespan [Two-stage hybrid flowshop scheduling problem, Oper. Res. Soc. 39 (1988) 359]. The research deals with the criterion of makespan minimization for the HFS scheduling problems. The operating parameters of meta-heuristics have an important role on the quality of the solution. In this paper we present a generic systematic procedure which is based on a multi-step experimental design approach for determining the optimum system parameters of AIS. AIS algorithm is tested with benchmark problems. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving HFS problems.