In recent years, several optimization methods especially metaheuristic optimization methods have been developed by scientists. People have utilized power of nature to solve problems. Therefore, those metaheuristic methods have imitated physical and biological processes of nature. In 2007, Big Bang Big Crunch optimization algorithm based on evolution of universe and in 2009, Gravitational Search...

A metaheuristic is generally a procedure designed to find a good solution to a difficult optimization problem. Known optimization search metaheuristics heavily rely on parameters, which are usually introduced so that the metaheuristic follows some supposedly related to the optimization problem natural process (simulated annealing, swarm optimization, genetic algorithms). Adjusting the parameter...

Variable Neighborhood Search (VNS) is a relatively new metaheuristic for solving hard combinatorial optimisation problems. One such optimisation problem is the Car Sequencing Problem (CarSP), where a sequence of cars along the assembly line with minimum production costs has to be found. Although VNS is a successful metaheuristic, it takes a long time until a suitable solution is found for real-...

Metaheuristics are truly diverse in nature — under the overarching theme of performing operations to escape local optima (we assume minima in this chapter without loss of generality), algorithms as different as ant colony optimization ([12]), tabu search ([16]), and genetic algorithms ([23]) have emerged. Due to the unique functionality of each type of metaheuristic, comparison of metaheuristic...

This paper presents an experimental investigation of the Sounds of Silence (SoS) harmony search metaheuristic for the multi-mode resource-constrained project scheduling problem (MRCPSP) using a pre-optimized starting repertoire. The presented algorithm is based on the time oriented version of the SoS harmony search metaheuristic developed by Csébfalvi et al. [1] for the single-mode resource-con...

Software verification and validation (V&V) activities are critical for achieving software quality; however, these activities also constitute a large part of the costs when developing software. Therefore efficient and effective software V&V activities are both a priority and a necessity considering the pressure to decrease time-to-market and the intense competition faced by many, if not all, com...

• We propose a process for the adaptation of service-oriented applications. • It is based on an optimization method. • It is based on trade-offs between functional and extra-functional requirements. • It uses metaheuristic search techniques and functional/extra-functional patterns. a r t i c l e i n f o a b s t r a c t Service-oriented applications may require adaptation to tackle changing user...

In order to improve the efficiency of test data generation during the software test, many studies have been focusing on the automation of test data generation with metaheuristic techniques such as genetic algorithm and tabu search etc. This paper proposes a hybrid algorithm in combination with genetic algorithm with tabu search to generate the test data based on decision coverage criteria. The ...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable approach to the problem is to encode it as a com...

We propose a control design scheme that aims to prevent undesirable liquid outpouring and suppress sloshing during the forward and backward tilting phases of the pouring process, for the case of liquid containers carried by manipulators. The proposed scheme combines a partial inverse dynamics controller with a PID controller, tuned with the use of a “metaheuristic” search algorithm. The “metahe...