Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near-optimal solution. The bat algorithm is one of the metaheuristic algorithms with poor exploration and exploitation. In this paper, exploration and ...

This study deals with performance-based design optimization (PBDO) of steel moment frames employing four different metaheuristics consisting of genetic algorithm (GA), ant colony optimization (ACO), harmony search (HS), and particle swarm optimization (PSO). In order to evaluate the seismic capacity of the structures, nonlinear pushover analysis is conducted (PBDO). This method is an iterative ...

this paper presents a new mathematical model for a redundancyallocation problem (rap) withcold-standby redundancy strategy and multiple component choices.the applications of the proposed model arecommon in electrical power, transformation,telecommunication systems,etc.manystudies have concentrated onone type of time-to-failure, butin thispaper, two components of time-to-failures which follow hy...

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 ...

the multiple traveling salesman problem (mtsp) involves scheduling m > 1 salesmen to visit a set of n > m nodes so that each node is visited exactly once. the objective is to minimize the total distance traveled by all the salesmen. the mtsp is an example of combinatorial optimization problems, and has a multiplicity of applications, mostly in the areas of routing and scheduling. in this paper,...

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...

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...

Railroad blocking problem (RBP) is one of the problems that need an important decision in freight railroads. The objective of solving this problem is to minimize the costs of delivering all commodities by deciding which inter-terminal blocks to build and by specifying the assignment of commodities to these blocks, while observing limits on the number and cumulative volume of the blocks assemble...

 Metaheuristic optimization has experienced an evolution toward the development of general purpose optimizers. Although the most effective metaheuristics for the solution of hard (in the computational sense) optimization problems are procedures customized to each particular situation, there is an increased interest in developing systems that can effectively operate as general-purpose solvers. ...