Publications related to Ant colony optimization algorithms

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Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Ant colony optimization algorithms

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Turning PathFinder Upside -Down: 1-4,xploring FPGA Switch -Blocks by Negotiating Switch Presence

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

Pareto-like sequential sampling heuristic for global optimisation

A General Framework for Optimal Data-Driven Optimization

Assessing the Impact of Transit Signal Priority Strategies on a Network

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Self-learning surrogate models in superstructure optimization

Inverse design of diffractive optical elements using step-transition perturbation approach

Convergence of adaptive algorithms for constrained weakly convex optimization

A General Framework for Optimal Data-Driven Optimization

Inverse design of diffractive optical elements using step-transition perturbation approach

Pareto-like sequential sampling heuristic for global optimisation

Turning PathFinder Upside -Down: 1-4,xploring FPGA Switch -Blocks by Negotiating Switch Presence

Convergence of adaptive algorithms for constrained weakly convex optimization

Assessing the Impact of Transit Signal Priority Strategies on a Network

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Self-learning surrogate models in superstructure optimization

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization