Bayesian optimization is an approach to optimizing objective functions that take a long time
(minutes or hours) to evaluate. It is best-suited for optimization over continuous domains of …

A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …

Conventional human-driven methods face limitations in designing complex functional
metasurfaces. Inverse design is poised to empower metasurface research by embracing fast …

Bayesian optimization is an approach to optimizing objective functions that take a long time
(minutes or hours) to evaluate. It is best suited for optimization over continuous domains of …

Variable neighborhood search (VNS) is a metaheuristic for solving combinatorial and global
optimization problems whose basic idea is a systematic change of neighborhood both within …

Abstract Travelling Salesman Problem (TSP) is an Np-Hard problem, for which various
solutions have been offered so far. Using the Harris Hawk Optimization (HHO) algorithm, this …

Nanophotonic devices have enabled microscopic control of light with an unprecedented
spatial resolution by employing subwavelength optical elements that can strongly interact …

This article focuses on synthesizing control policies for discrete-time stochastic control
systems together with a lower bound on the probability that the systems satisfy the complex …

Abstract The Artificial Bee Colony (ABC) algorithm is a swarm intelligence approach which
has initially been proposed to solve optimisation of mathematical test functions with a unique …

Abstract Traveling Salesman Problem (TSP) is an intricate discrete hybrid optimization
problem that is categorized as an NP‐Hard problem. The objective of the TSP is to find the …