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Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...

test functions for global optimizers". Mathworks. Retrieved 1 November 2012. Deb, Kalyanmoy (2002) Multiobjective optimization using evolutionary algorithms...

by using another overlaying optimizer, a concept known as meta-optimization, or even fine-tuned during the optimization, e.g., by means of fuzzy logic...

optimization of black-box functions using Bayesian statistics Deterministic global optimization Multidisciplinary design optimization Multiobjective optimization...

Multi-disciplinary design optimization (MDO) is a field of engineering that uses optimization methods to solve design problems incorporating a number...

Random optimization (RO) is a family of numerical optimization methods that do not require the gradient of the optimization problem and RO can hence be...

industrial optimization with the Faculty of Information Technology, University of Jyväskylä, Finland. In addition, she heads the Multiobjective Optimization Group...

which study infinite-dimensional optimization problems are calculus of variations, optimal control and shape optimization. Semi-infinite programming David...

possible. Local search is a sub-field of: Metaheuristics Stochastic optimization Optimization Fields within local search include: Hill climbing Simulated annealing...

sum method for multiobjective optimization: a new method for Pareto front generation". Structural and Multidisciplinary Optimization. 31 (2): 105–116...

design optimization is structural design optimization (SDO) is in building and construction sector. SDO emphasizes automating and optimizing structural...

Derivative-free optimization (sometimes referred to as blackbox optimization) is a discipline in mathematical optimization that does not use derivative...

In applied mathematics, multimodal optimization deals with optimization tasks that involve finding all or most of the multiple (at least locally optimal)...

Robust optimization is a field of mathematical optimization theory that deals with optimization problems in which a certain measure of robustness is sought...

Biogeography-based optimization (BBO) is an evolutionary algorithm (EA) that optimizes a function by stochastically and iteratively improving candidate...

Single- and Multi-population coevolution SPEA2 multiobjective optimization Particle Swarm Optimization Differential Evolution Spatially embedded evolutionary...

also used in other metaheuristics, such as ant colony optimization or particle swarm optimization. In the field of EAs, each candidate solution, also called...

of optimization methods that sample from a hypersphere surrounding the current position. Random optimization is a related family of optimization methods...

strategy for numerical optimization. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear or non-convex...

In the field of mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic...