A branch and bound algorithm for the job-shop scheduling problem
Discrete Applied Mathematics - Special volume: viewpoints on optimization
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
A fast taboo search algorithm for the job shop problem
Management Science
Neural network and genetic algorithm-based hybrid approach to expanded job-shop scheduling
Computers and Industrial Engineering
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling
Computers and Operations Research
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
A hybrid genetic algorithm for the job shop scheduling problems
Computers and Industrial Engineering
A new approach to solve hybrid flow shop scheduling problems by artificial immune system
Future Generation Computer Systems - Special issue: Computational science of lattice Boltzmann modelling
NP-complete scheduling problems
Journal of Computer and System Sciences
Adaptive immune algorithm for solving job-shop scheduling problem
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
A novel genetic algorithm based on immunity
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Single-machine scheduling with sum-of-logarithm-processing-times-based learning considerations
Information Sciences: an International Journal
Some single-machine and m-machine flowshop scheduling problems with learning considerations
Information Sciences: an International Journal
Baldwinian learning in clonal selection algorithm for optimization
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
An efficient memetic algorithm for solving the job shop scheduling problem
Computers and Industrial Engineering
Information Sciences: an International Journal
Structural design of the danger model immune algorithm
Information Sciences: an International Journal
A hybrid intelligent model for order allocation planning in make-to-order manufacturing
Applied Soft Computing
An optimal method for the preemptive job shop scheduling problem
Computers and Operations Research
A Novel Immune Optimization Algorithm for Fairness Resource Allocation in Cognitive Wireless Network
Wireless Personal Communications: An International Journal
A new hybrid artificial bee colony algorithm for robust optimal design and manufacturing
Applied Soft Computing
Planning of business process execution in Business Process Management environments
Information Sciences: an International Journal
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This paper describes the application of an artificial immune system to a scheduling application. A novel approach multi-modal immune algorithm is proposed for finding optimal solutions to job-shop scheduling problems emulating the features of a biological immune system. Inter-relationships within the proposed algorithm resemble antibody molecule structure, antibody-antigen relationships in terms of specificity, clonal proliferation, germinal center, and the memory characteristics of adaptive immune responses. Gene fragment recombination and several antibody diversification schemes including somatic recombination, somatic mutation, gene conversion, gene reversion, gene drift, and nucleotide addition were incorporated into the algorithm in order to improve the balance between exploitation and exploration. In addition, niche antibody was employed to discover multi-modal solutions. Numerous well-studied benchmark examples in job-shop scheduling problems were utilized to evaluate the proposed approach. The results indicate the effectiveness and flexibility of the immune algorithm.