P-Complete Approximation Problems
Journal of the ACM (JACM)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Exploiting Tabu Search Memory in Constrained Problems
INFORMS Journal on Computing
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
Application areas of AIS: The past, the present and the future
Applied Soft Computing
Information Sciences: an International Journal
Improved Clonal Selection Algorithm Combined with Ant Colony Optimization
IEICE - Transactions on Information and Systems
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
A continuous approach to considering uncertainty in facility design
Computers and Operations Research
Expert Systems with Applications: An International Journal
Solving traveling salesman problems by artificial immune response
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
A new mixed integer programming formulation for facility layout design using flexible bays
Operations Research Letters
Relationships of swarm intelligence and artificial immune system
International Journal of Bio-Inspired Computation
Hi-index | 12.05 |
This study introduces an artificial immune system (AIS) based algorithm to solve the unequal area facility layout problem (FLP) with flexible bay structure (FBS). The proposed clonal selection algorithm (CSA) has a new encoding and a novel procedure to cope with dummy departments that are introduced to fill the empty space in the facility area. The algorithm showed consistent performance for the 25 test problem cases studied. The problems with 100 and 125 were studied with FBS first time in the literature. CSA provided four new best FBS solutions and reached to sixteen best-so-far FBS solutions. Further, the two very large size test problems were solved first time using FBS representation, and results significantly improved the previous best known solutions. The overall results state that CSA with FBS representation was successful in 95.65% of the test problems when compared with the best-so-far FBS results and 90.90% compared with the best known solutions that have not used FBS representation.