This paper presents an improved extremal optimization (IEO) algorithm for solving the asymmetric traveling salesman problem (ATSP). At each update step, the IEO algorithm proceeds through two main steps: extremal dynamics and cooperative optimization. As an improvement of extremal optimization...

By mapping the optimization problems to physical systems, the paper presents a general-purpose stochastic optimization method with extremal dynamics. It is built up with the traveling salesman problem (TSP) being a typical NP-complete problem. As self-organized critical processes of extremal...

The adjustable parameters of probability distributions adopted by extremal optimization (EO) and its modified versions play a critical role in controlling their performances. Unlike the traditional static probability distribution based strategy, this paper presents a novel method called...

It is widely believed that the power-law is a proper probability distribution being effectively applied for evolution in τ-EO (extremal optimization), a general-purpose stochastic local-search approach inspired by self-organized criticality, and its applications in some NP-hard problems,...

Almost all natural, social and man-made-engineered systems can be represented by a complex network to describe their dynamic behaviors. To make a real-world complex network controllable with its desired topology, the study on network controllability has been one of the most critical and...

The purpose of this paper is to apply a belief rule-based (BRB) system to solve the multiasset class portfolio optimisation problems. The BRB system, was developed on the basis of the concept of belief structures and the evidential reasoning (ER) approach, is a generic non-linear modelling and...