Satellite Broadcast Scheduling Based on a Boosted Binary Differential Evolution

AbstractThe satellite broadcasts scheduling (SBS) optimization problem is known to be an NP-complete problem which like all scheduling, is the problem of mapping tasks to resources. The aim of this problem is to find a valid broadcasting pattern to earth-stationed terminals which maximizes the number of timeslots utilized for broadcasting under certain constraints. In this paper, we proposed Boosted Binary Differential Evolution (BBDE) to solve SBS and propose some various methods for every stage of the algorithm. Our proposed algorithm employs the best method in different stages of DE. The result of our algorithm is tested against published works toward solving SBS problem. A set of benchmark instances that reported in the literature for SBS problem are used to evaluate the performance of the proposed algorithm. The experimental results show that the BBDE algorithm has achieved good improvement on the optimization of SBS.

[1]  Andries Petrus Engelbrecht,et al.  Differential evolution methods for unsupervised image classification , 2005, 2005 IEEE Congress on Evolutionary Computation.

[2]  Joseph C. Pemberton,et al.  A constraint-based approach to satellite scheduling , 1998, Constraint Programming and Large Scale Discrete Optimization.

[3]  Hamid R. Tizhoosh,et al.  Opposition-Based Learning: A New Scheme for Machine Intelligence , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[4]  T. Tambouratzis.  Decomposition co-ordination artificial neural network for satellite broadcast scheduling , 1998 .

[5]  Nirwan Ansari,et al.  A new method to optimize the satellite broadcasting schedules using the mean field annealing of a Hopfield neural network , 1995, IEEE Trans. Neural Networks.

[6]  Mahamed G. H. Omran,et al.  Constrained optimization using CODEQ , 2009 .

[7]  M. Pant,et al.  TWO SELF ADAPTIVE VARIANTS OF DIFFERENTIAL EVOLUTION ALGORITHM FOR GLOBAL OPTIMIZATION , 2012 .

[8]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[9]  David E. Goldberg,et al.  Genetic Algorithms, Tournament Selection, and the Effects of Noise , 1995, Complex Syst..

[10]  Jung-Chieh Chen.  A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems , 2008, IEICE Trans. Commun..

[11]  Andrew Lewis,et al.  S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization , 2013, Swarm Evol. Comput..

[12]  Sandra Paterlini,et al.  High performance clustering with differential evolution , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[13]  Janez Brest,et al.  Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems , 2006, IEEE Transactions on Evolutionary Computation.

[14]  D. Karaboga,et al.  A Simple and Global Optimization Algorithm for Engineering Problems: Differential Evolution Algorithm , 2004 .

[15]  Minrui Fei,et al.  A Discrete Harmony Search Algorithm , 2010 .

[16]  Imtiaz Ahmad,et al.  A metaheuristic algorithm to solve satellite broadcast scheduling problem , 2015, Inf. Sci..

[17]  Pangan Ting,et al.  Factor Graphs for Satellite Broadcast Scheduling Problems , 2008, 2008 IEEE 68th Vehicular Technology Conference.

[18]  Mehmet Fatih Tasgetiren,et al.  An ensemble of discrete differential evolution algorithms for solving the generalized traveling salesman problem , 2010, Appl. Math. Comput..

[19]  Ponnuthurai N. Suganthan,et al.  A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems , 2010, Comput. Oper. Res..

[20]  M. Samuelides,et al.  Optimal scheduling by competitive activation: application to the satellite antennae scheduling problem , 1989, International 1989 Joint Conference on Neural Networks.

[21]  Tao Gong,et al.  Differential Evolution for Binary Encoding , 2007 .

[22]  Arthur C. Sanderson,et al.  Pareto-based multi-objective differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[23]  Ming-Shi Wang,et al.  Optimizing satellite broadcast scheduling problem using the competitive Hopfield neural network , 2007, 2007 Wireless Telecommunications Symposium.

[24]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[25]  Joseph C. Pemberton.  Towards scheduling over-constrained remote sensing satellites , 2000 .

[26]  Nobuo Funabiki,et al.  A binary Hopfield neural-network approach for satellite broadcast scheduling problems , 1997, IEEE Trans. Neural Networks.

[27]  Mahamed G. H. Omran.  CODEQ: an effective metaheuristic for continuous global optimisation , 2010, Int. J. Metaheuristics.

[28]  Xiaohui Yuan,et al.  Application of enhanced discrete differential evolution approach to unit commitment problem , 2009 .

[29]  Stefan Janaqi,et al.  Generalization of the strategies in differential evolution , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..