Optimization problems concern exploration of the best possible solutions to a given problem. The feasible solutions are termed good or bad based on the respective values of the objective function. For ...

An optimization protocol for solving the optimization problem in a distributed manner by application of a nonlinear incremental cost (IC) consensus method is proposed. The analysis for the proposed ...

This paper addresses the problem of optimizing a device by using an interpolation of the objective function. Optimization by means of stochastic methods can explore the objective function and give ...

By using the penalty function method with objective parameters, the paper presents an interactive algorithm to solve the inequality ... Z. Meng, R. Shen and M. Jiang, "An Objective Penalty Functions ...

My attempt was to combine the principles from tutorials/papers on Robust multi-objective Bayesian optimization under input noise and Risk averse Bayesian optimization with environmental ...

Noisy, discontinuous, or multimodal objective functions pose significant challenges for numerical optimization methods. These functions are often encountered in real-world problems, such as ...

Learn how to choose the best python optimization library for your project based on problem type, algorithm choice, and interface and usability. Compare popular and useful libraries and tools.

By using the penalty function method with objective parameters, the paper presents an interactive algorithm to solve the inequality constrained multi-objective programming (MP). The MP is transformed ...