An Ant Colony Algorithm Based on Cross-Layer Design for Routing and Wavelength Assignment in Optical Satellite Networks

This paper introduces an ant colony routing and wavelength assignment algorithm based on cross-layer design(CL-ACRWA),which can overcome the adverse effects of Doppler wavelength shift on data transmission in optical satellite networks. Firstly, a cross-layer optimization model is built, which considers the Doppler wavelength shift, the transmission delay as well as wavelength-continuity constraint. Then an ant colony algorithm is utilized to solve the cross-layer optimization model, resulting in finding an optimal light path satisfying the above constraints for every connection request. The performance of CL-ACRWA is measured by the communication success probability, the convergence property and the transmission delay. Simulation results show that CL-ACRWA performs well in communication success probability and has good global search ability as well as fast convergence speed. Meanwhile, the transmission delay can meet the basic requirement of real-time transmission of business.

Dynamic routing and wavelength assignment algorithm of optical satellite networks based on cross-layer design

In order to overcome the adverse effects of Doppler wavelength shift on data transmission in the optical satellite networks,a dynamic routing and wavelength assignment algorithm based on crosslayer design( CL-DRWA) is introduced which can improve robustness of the network. Above all,a cross-layer optimization model is designed,which considers transmission delay and wavelength-continuity constraint,as well as Doppler wavelength shift. Then CL-DRWA is applied to solve this model,resulting in finding an optimal light path satisfying the above constraints for every connection request. In CL-DRWA,Bellman-Ford method is used to find an optimal route and a distributed relative capacity loss method is implemented to get an optimal wavelength assignment result on the optimal route. Moreover,compared with the dynamic routing and wavelength assignment algorithm based on minimum delay strategy( MD-DRWA),CL-DRWA can make an improvement of 5. 3% on the communication success probability. Meanwhile,CL-DRWA can meet the requirement of transmission delay for real-time services.

Storage Assignment Optimization in a Multi-tier Shuttle Warehousing System

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retrieval system（AS/RS）.However,the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems（MSWS） because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP.In this study,a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period（SWP） and lift idle period（LIP） during transaction cycle time.A mean arrival time difference matrix for pairwise stock keeping units（SKUs） is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation.The decomposition method is applied to analyze the interactions among outbound task time,SWP,and LIP.The ant colony clustering algorithm is designed to determine storage partitions using clustering items.In addition,goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane.This combination is derived based on the analysis results of the queuing network model and on three basic principles.The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry.The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.

Competition Based Neural Networks for Assignment Problems

Competition based neural networks have been used to solve the generalized assignment problem andthe quadratic assignment problem.Both problems are very difficult and are ε approximation complete.Theneural network approach has yielded highly competitive performance and good performance for thequadratic assignment problem.These neural networks are guaranteed to produce feasible solutions.