Mathematical models of biological processes have various applications: to assist in
understanding the functioning of a system, to simulate experiments before actually …

The biological process and molecular functions involved in the cancer progression remain
difficult to understand for biologists and clinical doctors. Recent developments in high …

The algorithm described here, called OptQuest/NLP or OQNLP, is a heuristic designed to
find global optima for pure and mixed integer nonlinear problems with many constraints and …

The evolutionary approach called Scatter Search, and its generalized form called Path
Relinking, have proved unusually effective for solving a diverse array of optimization …

A major challenge in Bayesian Optimization is the boundary issue where an algorithm
spends too many evaluations near the boundary of its search space. In this paper, we …

Nowadays, the economy of countries highly depends on the agriculture productivity which
has a great effect on the development of human civilization. Sometimes, plant diseases …

A Rosenbrock artificial bee colony algorithm (RABC) that combines Rosenbrock's rotational
direction method with an artificial bee colony algorithm (ABC) is proposed for accurate …

Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific
computing. This book discusses recent developments of MCMC methods with an emphasis …

This paper provides a novel establishment method of the variable-fidelity surrogate model
(VFSM) driven by transfer learning for shell buckling prediction problems such as buckling …

Scatter search is an evolutionary method that has been successfully applied to hard
optimization problems. The fundamental concepts and principles of the method were first …