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...

The purpose of this article is to propose a perturbation metaheuristic for the Vehicle Routing Problem with Private fleet and Common carrier (VRPPC). This problem consists of serving all customers such in a way that 1) each customer is served exactly once either by a private fleet vehicle or by a common carrier vehicle, 2) all routes associated with the private fleet start and end at the depot,...

A novel robust hybrid metaheuristic optimization approach, which can be considered as an improvement of the recently developed bat algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of pitch adjustment operation in HS serving as a mutation operator during the process of the bat updating with the aim of speeding up convergence, thus maki...

The Graph Partitioning Problem (GPP) is one of the most studied NPcomplete problems notable for its broad spectrum of applicability such as in VLSI design, data mining, image segmentation, etc. Due to its high computational complexity, a large number of approximate approaches have been reported in the literature. Hybrid algorithms that are based on adaptations of popular metaheuristic technique...

Nature is a great source of inspiration for solving complex problems in networks. It helps to find the optimal solution. Metaheuristic algorithm is one of the nature-inspired algorithm which helps in solving routing problem in networks. The dynamic features, changing of topology frequently and limited bandwidth make the routing, challenging in MANET. Implementation of appropriate routing algori...

Metaheuristic algorithms are extensively recognized as effective approaches for solving high-dimensional optimization problems. These algorithms provide effective tools with important applications in business, engineering, economics, and science. This paper surveys state-of-the-art metaheuristic algorithms and their current applications in the field of large-scale global optimization. The paper...

A metaheuristic is a high-level problem-independent algorithmic framework that provides a set of guidelines or strategies to develop heuristic optimization algorithms (Sörensen and Glover, To appear). Notable examples of metaheuristics include genetic/evolutionary algorithms, tabu search, simulated annealing, and ant colony optimization, although many more exist. A problem-specific implementati...

GRASP, or greedy randomized adaptive search procedure, is a multi-start metaheuristic that repeatedly applies local search starting from solutions constructed by a randomized greedy algorithm. In this chapter we consider ways to hybridize GRASP to create new and more effective metaheuristics. We consider several types of hybridizations: constructive procedures, enhanced local search, memory str...

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 ...