The COPS test set provides a modest selection of difficult nonlinearly constrained optimization problems from applications in optimal design, fluid dynamics, parameter estimation, and optimal control. In this report we describe version 2.0 of the COPS problems. The formulation and discretization of the original problems have been streamlined and improved. We have also added new problems. The presentation of COPS follows the original report, but the description of the problems has been streamlined. For each problem we discuss the formulation of the problem and the structural data in Table 0.1 on the formulation. The aim of presenting this data is to provide an approximate idea of the size and sparsity of the problem. We also include the resu...
The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching...
In almost all scientific contributions to the field of Nature-Inspired Algorithms (NIAs), the resear...
As a first step to the realization of a new computer program to solve general nonlinear optimization...
The authors describe version 3.0 of the COPS set of nonlinearly constrained optimization problems. T...
The authors have started the development of COPS, a collection of large-scale nonlinearly Constraine...
This paper introduces the COPSO algorithm (Constrained Optimization via Particle Swarm Opti-mization...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
The purpose of this article is to discuss the scopeand functionality of a versatile environment for ...
A large number of problems in Artificial Intelligence and other areas of science can be viewed as sp...
Most real world optimization problems, and their corresponding models, are complex. This complexity ...
The availability of nonlinear programming test problems is extremely important to test optimization ...
The experimental results reported in many papers suggest that making an appropriate a priori choice ...
This paper develops a particle swarm optimization (PSO) based framework for constrained optimization...
This repository contains the source code for the algorithm designed to learn on-the-fly (variable or...
This paper investigates application of SQP optimization algorithms to nonlinear model pre-dictive co...
The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching...
In almost all scientific contributions to the field of Nature-Inspired Algorithms (NIAs), the resear...
As a first step to the realization of a new computer program to solve general nonlinear optimization...
The authors describe version 3.0 of the COPS set of nonlinearly constrained optimization problems. T...
The authors have started the development of COPS, a collection of large-scale nonlinearly Constraine...
This paper introduces the COPSO algorithm (Constrained Optimization via Particle Swarm Opti-mization...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
The purpose of this article is to discuss the scopeand functionality of a versatile environment for ...
A large number of problems in Artificial Intelligence and other areas of science can be viewed as sp...
Most real world optimization problems, and their corresponding models, are complex. This complexity ...
The availability of nonlinear programming test problems is extremely important to test optimization ...
The experimental results reported in many papers suggest that making an appropriate a priori choice ...
This paper develops a particle swarm optimization (PSO) based framework for constrained optimization...
This repository contains the source code for the algorithm designed to learn on-the-fly (variable or...
This paper investigates application of SQP optimization algorithms to nonlinear model pre-dictive co...
The hurdles in solving Constrained Optimization Problems (COP) arise from the challenge of searching...
In almost all scientific contributions to the field of Nature-Inspired Algorithms (NIAs), the resear...
As a first step to the realization of a new computer program to solve general nonlinear optimization...