Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algori...

the travelling salesmen problem (tsp) is one of the most important and famous combinational optimization problems that aim to find the shortest tour. in this problem, the salesman starts to move from an arbitrary place called depot and after visiting all nodes, finally comes back to depot. solving this problem seems hard because program statement is simple and leads this problem belonging to np...

wireless sensor networks are the new generation of networks that typically are formed great numbers of nodes and the communications of these nodes are done as wireless. the main goal of these networks is collecting data from neighboring environment of network sensors. since the sensor nodes are battery operated and there is no possibility of charging or replacing the batteries, the lifetime of ...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. In this paper, a bi-objective mathematical model is proposed to design a network of preventive healthcare facilities so as to minimize total travel and waiting time as well as establishment and staffing cost. Moreover, each facility acts as M/M/1 queuin...

Flood is a common global natural hazard, and detailed flood susceptibility maps for specific watersheds are important management measures. We compute the map Kaiser watershed in Iran using machine learning models such as support vector (SVM), Particle swarm optimization (PSO), genetic algorithm (GA) along with ensembles (PSO-GA SVM-GA). The application of assessment mapping analyzed, future res...

The p-median problem is one of the discrete optimization problem in location theory which aims to satisfy total demand with minimum cost. A high-level algorithmic approach can be specialized to solve optimization problem. In recent years, meta-heuristic methods have been applied to support the solution of Combinatorial Optimization Problems (COP). Collision Bodies Optimization algorithm (CBO) a...