In this paper an accurate method is presented for determining of the device sizes in a RF circuit based on genetic algorithm (GA). HSPICE RF simulation is used for evaluating of the fitness of the circuit specifications per every iteration of the GA. Also an example for a LNA is presented for evaluating of non-dominated sorting genetic algorithm (NSGA-II) as a method of multi objective genetic ...

To improve customer satisfaction of cold chain logistics fresh agricultural goods enterprises and reduce the comprehensive distribution cost composed fixed cost, transportation cargo damage refrigeration time penalty a multi-objective path optimization model products considering client is constructed. The solved using an enhanced Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), differ...

In this paper we propose two novel approaches for solving constrained multi-objective optimization problems using steady state GAs. These methods are intended for solving real-world application problems that have many constraints and very small feasible regions. One method called Objective Exchange Genetic Algorithm for Design Optimization (OEGADO) runs several GAs concurrently with each GA opt...

This study addresses the pickup and delivery problem for cross-docking strategy, in which shipments are allowed to be transferred from suppliers to retailers directly as well as through cross-docks. Usual models that investigate vehicle routing in cross-docking networks force all vehicles to stop at the cross-dock even if a shipment is about to a full truckload or the vehicle collects and deliv...

One main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. This paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. Indeed, the nature of products is considered different and hub capacity constraint is also applied. Due to ...

Deception problems are among the hardest problems to solve using ordinary genetic algorithms. Designed to simulate a high degree of epistasis, these deception problems imitate extremely difficult real world problems. [1]. Studies show that Bayesian optimization and explicit building block manipulation algorithms, like the fast messy genetic algorithm (fmGA), can help in solving these problems. ...

The uncertainty of transportation duration between nodes is an inherent characteristic and should be concerned in the routing optimization multimodal network to guarantee reliability delivery time. interval number used deal with duration, multi-objective robust model established which covers cost. To solve combinatorial problem this study, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) de...

distribution centers (dcs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.this paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. an evolutionary algorithm named non-dominated sorting ant colony optimization (nsaco) is used as the optimi...