Embedded Files
Computational Metabolic Engineering
Computational Metabolic Engineering
OptKnock, M-OptKnock, OptYield, and M-OptYield
OptKnock, M-OptKnock, OptYield, and M-OptYield
Description: Tools developed for identification of knockout targets for metabolic engineering
Source code: implemented in the MATLAB Cobra toolbox (download here)
Network Interdiction + Benders Decomposition (NIHBA)
Network Interdiction + Benders Decomposition (NIHBA)
Description: Benders decompsition to identify multiple strain design strategies in one go.
Source code: implemented in the MATLAB Cobra toolbox
Evolutionary Computation
Evolutionary Computation
competition
DF test suite: 2018 CEC Dynamic Multiobjecitve Optimisation Competition
DF test suite: 2018 CEC Dynamic Multiobjecitve Optimisation Competition
Description: 14 DF functions are used for the competion
More details: ncl website (click here),
AREA representation
AREA: Adaptive Reference guided Evolutionary Algorithm
AREA: Adaptive Reference guided Evolutionary Algorithm
Description: A new framework using adaptive references as search targets for candidates to approach.
Source code: Matlab (download here)
Links to application
SDP: Scalable Dynamic Multiobjective Problems
SDP: Scalable Dynamic Multiobjective Problems
Description: A test suite for scalable dynamic multiobjective optimisation competition.
Source code: Matlab, C++ (download here)
Dynamic changes
DF: CEC2018 Competition on Dynamic Multiobjective Optimisation
DF: CEC2018 Competition on Dynamic Multiobjective Optimisation
Description: A test suite for CEC2018 dynamic multiobjective optimisation competition.
Source code: Matlab (download here), C++ (download here)
Scalarizing Function
eMOEA/D: Scalarizing functions in decomposition- based evolutionary algorithms
eMOEA/D: Scalarizing functions in decomposition- based evolutionary algorithms
Description: improved MOEA/D with effective scalarising functions for multi-objective optimisation
Source code: Matlab, C++
Diversity Sorting
SPEA/R: Strength Pareto Evolutionary Algorithm based on Reference Directions
SPEA/R: Strength Pareto Evolutionary Algorithm based on Reference Directions
Description: an algorithm employs reference directions to perform diversity first and convergence second environmental selection for multi and many-objective optimisation
Source code: Matlab, C++
IGD vs Changes
SGEA: A steady-state and generational evolutionary algorithm for dynamic multiobjective optimization
SGEA: A steady-state and generational evolutionary algorithm for dynamic multiobjective optimization
Description: evolutionary algorithm dealing with dynamic multiobjective problems in a steady-state and generational manner.
Source code: Matlab, C++
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