location-allocation is a combinatorial optimization problem, and is defined as non deterministic polynomial hard (np) hard optimization. therefore, solution of such a problem should be shifted from exact to heuristic or meta heuristic due to the complexity of the problem. locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster managem...

offshore jacket-type towers are steel structures designed and constructed in marine environments for various purposes such as oil exploration and exploitation units, oceanographic research, and undersea testing. in this paper a newly developed meta-heuristic algorithm, namely cyclical parthenogenesis algorithm (cpa), is utilized for sizing optimization of a jacket-type offshore structure. the a...

Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem. Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms. Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve differenttypes of NP-hard problems.However, ant colony s...

Deterring the optimum design of large-scale structures is a difficult task. Great number of design variables, largeness of the search space and controlling great number of design constraints are major preventive factors in performing optimum design of large-scale truss structures in a reasonable time. Meta-heuristic algorithms are known as one of the useful tools to d...

periodic vehicle routing problem focuses on establishing a plan of visits to clients over a given time horizon so as to satisfy some service level while optimizing the routes used in each time period. This paper presents a new effective heuristic algorithm based on data mining tools for periodic vehicle routing problem (PVRP). The related results of proposed algorithm are compared with the resu...

The problem of searching for the best values ​​of fuzzy logic parameters (T1FLS) is consider complex problems, and type-2 system (T2FLS) more complex, in special case interval (IT2FLS). Researchers have used many methods algorithms to solve this problem, among most important field are the)Meta-heuristic) algorithms. Because Meta-heuristic a high capacity practical field, so we one modern which ...

Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...

Deep learning (DL) is a type of machine learning that mimics the thinking patterns of a human brain to learn the new abstract features automatically by deep and hierarchi‐ cal layers. DL is implemented by deep neural network (DNN) which has multihidden layers. DNN is developed from traditional artificial neural network (ANN). However, in the training process of DL, it has certain inefficiency d...

Background Many combinatorial optimization problems are NP-hard, and the theory of NP-completeness has reduced hopes that NP-hard problems can be solved within polynomially bounded computation times (Dahlke 2008; Dunne 2008). Nevertheless, sub-optimal solutions are sometimes easy to find. Consequently, there is much interest in approximation and heuristic algorithms that can find near optimal s...

The vehicle routing problem (VRP), a well-known combinatorial optimization problem, holds a central place in logistics management. Many meta-heuristic approaches like Simulated Annealing (SA), Genetic Algorithms (GA), Tabu Search (TS), and Ant Colony Optimization (ACO) have been proposed to solve VRP. Ant Algorithm is a distributed meta-heuristic approach that has been applied to various combin...