wireless sensor networks, due to the characteristics of sensors such as wireless communication channels, the lack of infrastructure and targeted threats, are very vulnerable to the various attacks. routing attacks on the networks, where a malicious node from sending data to the base station is perceived. in this article, a method that can be used to transfer the data securely to prevent attacks...

various synthesis methods have been proposed in the literature for reversible and quantum logic circuits. however, there are few algorithms to optimize an existing circuit with multiple constraints simultaneously. in this paper, some heuristics in genetic algorithms (ga) to optimize a given circuit in terms of quantum cost, number of gates, location of garbage outputs, and delay, are proposed. ...

the finite element method (fem) is one of advanced methods in modeling of solid mechanics used in the design and analyzing of prosthesis in the human body. one of the important factors in designing a femur (the linkage between basin and knee) which is under complicated stresses is to minimize the amount of the stress in the components of the prosthesis due to the body weight. in this research t...

A sorting algorithm defines a path in the search space of n! permutations based on the information provided by a comparison predicate. Our generic mutation operator for hybridization, blends a hill-climber and follows the path traced by any sorting algorithm. Our proposal adds search (exploitation) capability to the mutation operator. Mutation requests swaps to construct and test new permutatio...

Genetic algorithms derived from observations of nature and simulation of artificial selection of organisms with multiple loci that control a measurable trait. To date, genetic algorithms evolved into complex and strong informatics tools able to deal with hard problems of decision, classification, optimization and simulation. A series of studies reported biotechnology hard problems solved using ...

In recent years, the trend in solving optimization problems has been directed toward using heuristic algorithms such as neural networks, genetic and ant colony algorithms. The main reason for this trend can be attributed to the fact that these algorithms can be efficiently adjusted to the specific search space to which they are applied and consequently they can be used for many optimization pro...

We briefly review previous attempts to generate near-optimal solutions of the Traveling Salesman Problem by applying Genetic Algorithms. Following the lines of Johnson [1990] we discuss some possibilities for speeding up classical Local Search algorithms by casting them into a genetic frame. In an experimental study two such approaches, viz. Genetic Local Search with 2-Opt neighbourhoods and Li...

This paper presents a novel, integer-linear programming (ILP) model for an identical parallel-machine scheduling problem with family setup times that minimizes the total weighted flow time (TWFT). Some researchers have addressed parallel-machine scheduling problems in the literature over the last three decades. However, the existing studies have been limited to the research of independent jobs,...

|A novel evolutionary computing method | quantum inspired genetic algorithms | is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more eecient evolutionary computing methods. The basic terminology of quantum mechanics is introduced before a comparison is made between a classical genetic algorithm and a quantum inspired method for the travelling sale...