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With the emergence of wireless networking paradigm, several optimization problems are showing their usefulness to the efficient design of such networks. These problem are related, among others, to optimizing network connectivity, coverage and stability. The resolution of these problems turns out to be crucial for optimized network performance. In the case of Wireless Mesh Networks (WMN), such problems...
Solving large-scale structural design and damage identification problems using genetic algorithm optimization methods requires the use of advanced representations. The flexible implicit redundant representation (IRR) provides significant benefits for inverse problems in which the solution involves determining the optimal number of design variables, in addition to their values. The IRR encodes both...
Node placement problems have been long investigated in the optimization field due to numerous applications in facility location, logistics, services, etc. Such problems are attracting again the attention of researchers now from the networking domain, and more especially from Wireless Mesh Networks (WMNs) field. Indeed, the placement of mesh routers nodes appears to be crucial for the performance and...
In this paper, a novel optimization algorithm, named group search optimizer (GSO) with two improvements, is used to truss structure topology optimization. And the improved methods are using harmony memory and adhering to the boundary which can improve the algorithm obviously. Then a simple and effective topology method, discretization of topology variables is incorporated with improved GSO to make...
This paper present a new approach, combined pseudo- parallelism evolution technique based on sub-population competition with parent mutation mechanism, for automatic topology optimization of multilayer feedforward neural networks. It allows that two networks with different number of individuals can be crossed to a new valid "child" network. The calculation result of an example shows that...
The uncertainty in many engineering problems can be handled through probabilistic, fuzzy, or interval methods. This paper aims to use a hybrid genetic algorithm for tackling such problems. The proposed hybrid algorithm integrates a simple local search strategy as the worst-case-scenario technique of anti-optimization with a constrained multi-objective evolutionary algorithm. The work demonstrates...
A new bi-objective optimization problem is formulated for generating the diverse topologies of compliant mechanisms tracing a user-defined path. Motivation behind the present study is to generate the compliant mechanisms which perform the same task of tracing a prescribed trajectory near minimum-weight solution. Therefore, the constraint are imposed at each precision point representing a prescribed...
A major issue in software testing is the automatic generation of the inputs to be applied to the programme under test. To solve this problem, a number of approaches based on search methods have been developed in the last few years, offering promising results for adequacy criteria like, for instance, branch coverage. We devise branch coverage as the satisfaction of a number of constraints. This allows...
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