The conventional Unconstrained Binary Quadratic Programming (UBQP) problem is known to be a unified modeling and solution framework for many combinatorial optimization problems. This paper extends the single-objective UBQP to the multiobjective case (mUBQP) where multiple objectives are to be optimized simultaneously. We propose a hybrid metaheuristic which combines an elitist evolutionary mult...

This paper presents an FPGA-based (field-programmable gate array) hybrid metaheuristic GA (genetic algorithm)-PSO (particle swarm optimization) algorithm for mobile robots to find an optimal path between a starting and ending point in a grid environment. GA has been combined with PSO in evolving new solutions by applying crossover and mutation operators on solutions constructed by particles. Th...

The DNA sequencing problem is aimed at reconstructing an unknown fragment of DNA (deoxyribonucleic acid) based upon a set of oligonucleotides that makes up the fragment’s spectrum. Such a spectrum is the result of a hybridization experiment, in which oligonucleotides hybridize with the unknown DNA sequence. The introduction of errors (positive as well as negative) in the biological experiment p...

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition...

The n-queens problem is a classical combinatorial optimization problem which has been proved to be NP-hard. The goal is to place n non-attacking queens on an n×n chessboard. In this paper, the Imperialist Competitive Algorithm (ICA), which is a recent evolutionary metaheuristic method, has been applied for solving the n-queens problem. As another variation, the ICA was combined with a local sea...

Abstract This study proposes the Fire Hawk Optimizer (FHO) as a novel metaheuristic algorithm based on foraging behavior of whistling kites, black kites and brown falcons. These birds are termed Hawks considering specific actions they perform to catch prey in nature, specifically by means setting fire. Utilizing proposed algorithm, numerical investigation was conducted 233 mathematical test fun...

Nowadays genetic algorithms stand as a trend to solve NPcomplete and NP-hard problems. In this paper, we present a new hybrid metaheuristic which uses Parallel Genetic Algorithms and Scatter Search coupled with a decomposition-into-petals procedure for solving a class of Vehicle Routing and Scheduling Problems. The parallel genetic algorithm presented is based on the island model and was run on...

Sudoku is a notorious logic-based puzzle that is popular with puzzle enthusiasts the world over. From a computational perspective, Sudoku is also a problem that belongs to the set of NP-complete problems, implying that we cannot hope to find a polynomially bounded algorithm for solving the problem in general. Considering this feature, in this paper we demonstrate how a metaheuristic-based metho...

Metaheuristic algorithms such as particle swarm optimization, firefly algorithm and harmony search are now becoming powerful methods for solving many tough optimization problems. In this paper, we propose a new metaheuristic method, the Bat Algorithm, based on the echolocation behaviour of bats. We also intend to combine the advantages of existing algorithms into the new bat algorithm. After a ...

In this contribution we present a study on the combination of Differential Evolution and the IPOP-CMAES algorithms. The hybrid algorithm has been constructed by using theMultiple Offspring Sampling framework, which allows the seamless combination of multiple metaheuristics in a dynamic algorithm capable of adjusting the participation of each of the composing algorithms according to their curren...