the main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. recently there have been attempts for using artificial neural networks (anns) in optimizationproblems and some types of anns such as hopfield network and boltzm...

We introduce a new class of inverse optimization problems in which an input solution is given together with k linear weight functions, and the goal to modify weights by same deviation vector p so that becomes optimal respect each them, while minimizing ‖p‖1. In particular, we concentrate on three multiple functions: shortest s−t path, bipartite perfect matching, arborescence problems. Using LP ...

double bridge girder overhead cranes are used for heavy duty applications in theindustry. in this paper a detailed parametric design optimization of the main girder of box type isperformed for a 150ton capacity and 32m long span crane, after its basic design using availabledesign rules. design optimization is performed using detailed 3d finite element analysis bychanging the number, shape and l...

Particle Swarm Optimization algorithm (PSO) is found to be an effective meta-heuristic swarm-based in solving modern time problems. Various improvements have been proposed this terms of internal computation, acceleration coefficients, stopping criteria, hybridization, velocity upgradation etc. The objective paper implement hybrid weights and, therefore, improve the quality PSO algorithm. In cas...

Water cycle algorithm (WCA) is a new metaheuristic algorithm which the fundamental concepts of WCA are derived from nature and are based on the observation of water cycle process and how rivers and streams flow to sea in the real world. In this paper, the task of sizing optimization of truss structures including discrete and continues variables carried out using WCA, and the optimization result...