This paper proposes a hybrid genetic algorithm (GA) to solve the capacitated location–routing problem. The proposed algorithm follows the standard GA framework using local search procedures in the mutation phase. Computational evaluation was carried out on three sets of benchmark instances from the literature. Results show that, although relatively simple, the proposed algorithm is effective, p...

Global routing for VLSI circuits has received wide attraction. In this paper we have presented a Hybrid CHC (HCHC) genetic algorithm for global routing. The hybridization is required for initializing population with feasible solutions. The CHC algorithm is used for evolution. The algorithm was tested for standard test problems and compared with a simple GA. The CHC identified trees very nearer ...

As we know rice is the main food in China. In recent years, the rapid development of agricultural decision support system provides new management methods for rice production. GA has been regarded as an effective analytic tool and stochastic search technique to solve large and complicated problems. However, traditional GA-based decision support system does not always result in good solutions and...

−We investigate the performance of a classical constrained optimisation (CCO) algorithm and a constrained optimisation Genetic Algorithm (GA) for solving the Bandwidth Allocation for Virtual Paths (BAVP) problem. We compare throughput, fairness and time complexity of GA-BAVP and CCO-BAVP for several node topologies. The results on maximising the throughput obtained with GA-BAVP and CCOBAVP are ...

We propose a powerful Reinforced Hybrid Genetic Algorithm (RHGA) for the famous NP-hard Traveling Salesman Problem (TSP). RHGA combines reinforcement learning technique with well-known Edge Assembly Crossover genetic algorithm (EAX-GA) and Lin-Kernighan-Helsgaun (LKH) local search heuristic. With help of proposed hybrid mechanism, evolution EAX-GA LKH can boost each other's performance. And bas...

In this study a hybrid differential evolution-back-propagation algorithm to optimize the weights of feedforward neural network is proposed.The hybrid algorithm can achieve faster convergence speed with higher accuracy. The proposed hybrid algorithm combining differential evolution (DE) and back-propagation (BP) algorithm is referred to as DE-BP algorithm to train the weights of the feed-forward...

Network on Chip (NoC) architectures have emerged in recent years as scalable communication fabrics to enable high bandwidth data transfers in chip multiprocessors (CMPs). These interconnection architectures still need to conquer many challenges, e.g., significant power consumption and high data transfer latencies. Hybrid electro-photonic NoCs have been recently proposed as a solution to mitigat...

Numerous plant hormones interact during plant growth and development. Elucidating the role of these various hormones on particular tissue types or developmental stages has been difficult with exogenous applications or constitutive expression studies. Therefore, we used tissue-specific promoters expressing CKX1 and gai, genes involved in oxidative cytokinin degradation and gibberellin (GA) signa...

Stock market indices prediction is one of the most important issues in the financial field. Although many prediction models have been developed during the last decade, they suffer a poor performance because indices movement is highly non stationary and volatile dynamic process. As improving the prediction accuracy becomes an important issue, we propose a new hybrid genetic Algorithm / Particle ...

An integrated process which is proposed for improving dust removal efficiency of cyclones in another paper is considered here for simulation by Artifitial Neural Networks (ANNs) and hybrid ANN and Genetic Algorithm (GA). The process incorporates of two cyclones coupled with a specially designed cylindrical chamber, which includes a rotating tube inside it with air-impinging nozzles drilled on t...