Performance on Iter. by Jamilu Yahaya (18563445)

“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”

Greedy optimization algorithm. by Alexis Bénichou (19832361)

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

DataSheet1_Stochastic and Iterative Based Optimization for Enhancing Dynamic Performance of Interconnected Power System With Hybrid Energy Storage.docx by Niveditha Sivadanam (12328148)

“…This study proposes a stochastic and iterative based optimization for a two-area interconnected power system (IPS) coupled with a hybrid energy storage system (HESS). …”

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement - Fig 4 by Antoine Falisse (6061601)

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement - Fig 3 by Antoine Falisse (6061601)

Parallel plot showing hyperparameter exploration. by Ramona Leenings (11167294)

Buffer allocation problem in production flow lines: A new Benders-decomposition-based exact solution approach by Mengyi Zhang (7454231)

“…The algorithm iterates between a simulation module that generates the Benders cuts and an optimization module that involves the solution of an updated MILP model. …”

2DBPP modifications. by Andrew Fisher (1673086)

Notation example. by Andrew Fisher (1673086)

Swarm intelligence algorithms for multi-objective IMP by Francisco Muñoz (9455441)

Results of simulating the ability of pBO, BO and random search algorithms on identifying the optima in the Hartmann 3-dimensional surface. by Nienke E. R. van Bueren (11414330)

Optimization traces for six datasets and four NMTF optimization methods. by Andrej Čopar (6824375)

Performance of pairing prediction versus training set size and number of pairs per species. by Guillaume Marmier (7495823)

Manhattan plot of the univariate <i>p</i>-values for body mass index. by Junyang Qian (9558026)

Manhattan plot of the univariate <i>p</i>-values for asthma. by Junyang Qian (9558026)

Manhattan plot of the univariate <i>p</i>-values for height. by Junyang Qian (9558026)

Manhattan plot of the univariate <i>p</i>-values for high cholesterol. by Junyang Qian (9558026)

Description of the real-world dataset. by Fadi K. Dib (5204807)

“…Unlike most population-based methods, Jaya algorithm is a parameter-less algorithm in that it requires no algorithm-specific control parameters and only population size and number of iterations need to be specified, which makes it easy for researchers to apply in the field. …”

Screenshot of our visualization tool MGDrawVis. by Fadi K. Dib (5204807)

“…Unlike most population-based methods, Jaya algorithm is a parameter-less algorithm in that it requires no algorithm-specific control parameters and only population size and number of iterations need to be specified, which makes it easy for researchers to apply in the field. …”