Introduction

Abstract

Optimization problems are ubiquitous in academic research and real-world applications such as in engineering, finance, and scientific areas. What coefficients of a neural network minimize classification errors? What combination of bids maximizes the outcome in an auction? What variable- and check-node distributions optimize a low-density parity-check code design? In general, optimization problems arise wherever such resources as space, time and cost are limited. With no doubt, researchers and practitioners need an efficient and robust optimization approach to solve problems of different characteristics that are fundamental to their daily work.