The Portfolio selection problem is a relevant problem arising in finance and economics. Some practical formulations of the problem include various kinds of nonlinear constraints and objectives and can be efficiently solved by approximate algorithms. Among the most effective approximate algorithms, are metaheuristic methods that have been proved to be very successful in many applications. This ...

The Low Autocorrelation Binary Sequence problem has applications in telecommunications, is of theoretical interest to physicists, and has inspired work by many optimisation researchers because of its difficulty. For many years it was considered unsuitable for solution by metaheuristics because of its search space topology, but in recent years metaheuristics have found long high-quality sequence...

Nature-inspired metaheuristic algorithms have attracted much attention in the last decade, and new algorithms have emerged almost every year with a vast, ever-expanding literature. In this chapter, we briefly review two latest metaheuristics: bat algorithm and cuckoo search for global optimization. Bat algorithm was proposed by Xin-She Yang in 2010, inspired by the echolocation of microbats, wh...

A large number of metaheuristics inspired by natural and social phenomena have been proposed in the last few decades, each trying to be more powerful innovative than others. However, there is a lack accessible tools analyse, contrast visualise behaviour when solving optimisation problems. When metaphors are stripped away, these algorithms different their behaviour? To help answer this question,...

In recent years, several high-performance nature-inspired metaheuristic algorithms have been proposed. It is important to study and compare the convergence, computational burden statistical significance of these metaheuristics aid future developments. This focuses on six metaheuristics, namely, ant lion optimization (ALO), arithmetic algorithm (AOA), dragonfly (DA), grey wolf optimizer (GWO), s...

Difficult combinatorial optimization problems coming from practice are nowadays often approached by hybrid metaheuristics that combine principles of classical metaheuristic techniques with advanced methods from fields like mathematical programming, dynamic programming, and constraint programming. If designed appropriately, such hybrids frequently outperform simpler “pure” approaches as they are...

This paper outlines our findings concerning the use of constraints as design drivers in a design exploration process and investigates a possible application of a heuristic search and optimization method in architecture as a means for constraint solving. Fundamental theoretical research will cover these two aspects, accompanied with an appropriate test-case. Ghent University, Belgium

The fixed charge transportation problem (FCTP) is a deployment of the classical transportation problem in which a fixed cost is incurred, independent of the amount transported, along with a variable cost that is proportional to the amount shipped. Since the problem is considered as an NP-hard, the computational time grows exponentially as the size of the problem increases. In this pape...

Metaheuristics have been acknowledged as an effective solution for many difficult issues related to optimization. The metaheuristics, especially swarm’s intelligence and evolutionary computing algorithms, gained popularity within a short time over the past two decades. Various metaheuristics algorithms are being introduced on annual basis applications that more new gradually discovered. This pa...