In this paper multi objective optimization problem for partitioning process of VLSI circuit optimization is solved using IPO algorithm. The methodology used in this paper is based upon the dynamic of sliding motion along a frictionless inclined plane. In this work, modules and elements of the circuit are divided into two smaller parts (components) in order to minimize the cutsize and area imbal...

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...

Passive systems are preferred tools for seismic control of buildings challenged by probabilistic nature of the input excitation. However, other types of uncertainty still exist in parameters of the control device even when optimally tuned. The present work concerns optimal design of multiple-tuned-mass-damper embedded on a shear building by a number of meta-heuristics. They include well-known g...

Robots are now widely used in product disassembly lines, which significantly improves end-of-life (EOL) efficiency. Most of the current research on line balancing problems focuses decomposing one product. More than can be disassembled concurrently, further improve Moreover, uncertainty such as depreciation EOL products, may result failure. In this research, a stochastic multi-product robotic mo...

Energy-saving scheduling is a well-known issue in the manufacturing system. The flexibility of workshop increases difficulty scheduling. In schedule, considering collaborative optimization multi-level structure product production and energy consumption has certain practical significance. process sequence parts components should be consistent with assembly sequence. Additionally, non-production ...

To address the shortcomings of basic Gray Wolf Optimization (GWO) algorithm in solving complex problems, such as relying on initial population, converging too early, and easily falling into local optimality, a chaotic reverse learning initialization strategy, nonlinear control parameter convergence dynamic position update strategy are introduced to develop multi-strategy fusion Improved (IGWO) ...