Solving the task assignment problem with ant colony optimisation incorporating ideas from the clonal selection algorithm

The task assignment problem commonly appears in distributed computing environments. It asks an assignment of tasks to processors is found such that it satisfies the imposed constraints and that the total execution and communication cost of the tasks is minimal. This paper presents an algorithm based on ant colony optimisation that incorporates ideas from the clonal selection algorithm. Namely, the ant colony optimisation algorithm includes the cloning of the iteration-best ant and mutation of its clones' solutions; the goal being a better exploitation of promising parts of the search space. Besides that, the solution construction procedure is modified to take the memory constraints into account and the pheromone update mechanism is modified to enable the best clone to deposit pheromone. The experimental analysis, conducted on a large number of problem instances, showed that the proposed algorithm performs better compared to the MAX-MIN ant system, a differential evolution and a particle swarm optimisation algorithm.

[1]  Shahid H. Bokhari,et al.  A Shortest Tree Algorithm for Optimal Assignments Across Space and Time in a Distributed Processor System , 1981, IEEE Transactions on Software Engineering.

[2]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

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

[4]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[5]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[6]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[7]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[8]  Imtiaz Ahmad,et al.  Particle swarm optimization for task assignment problem , 2002, Microprocess. Microsystems.

[9]  Jonathan Timmis,et al.  Artificial immune systems - a new computational intelligence paradigm , 2002 .

[10]  F. Azuaje.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[11]  Amit Konar,et al.  Two improved differential evolution schemes for faster global search , 2005, GECCO '05.

[12]  Albert Mo Kim Cheng,et al.  Applying Ant Colony Optimization to the partitioned scheduling problem for heterogeneous multiprocessors , 2005, SIGBED Rev..

[13]  Simon M. Garrett,et al.  How Do We Evaluate Artificial Immune Systems? , 2005, Evolutionary Computation.

[14]  Michel Gendreau,et al.  Metaheuristics in Combinatorial Optimization , 2022 .

[15]  Peng-Yeng Yin,et al.  A hybrid particle swarm optimization algorithm for optimal task assignment in distributed systems , 2006, Comput. Stand. Interfaces.

[16]  Marco Dorigo,et al.  Ant colony optimization , 2006, IEEE Computational Intelligence Magazine.

[17]  Pin Luarn,et al.  A discrete version of particle swarm optimization for flowshop scheduling problems , 2007, Comput. Oper. Res..

[18]  Chukwudi Anyakoha,et al.  A review of particle swarm optimization. Part I: background and development , 2007, Natural Computing.

[19]  Ajay D. Kshemkalyani,et al.  Distributed Computing: Principles, Algorithms, and Systems , 2008 .

[20]  Xin Wang,et al.  A novel global harmony search algorithm for task assignment problem , 2010, J. Syst. Softw..

[21]  Thomas Stützle,et al.  Ant Colony Optimization: Overview and Recent Advances , 2018, Handbook of Metaheuristics.

[22]  Sadan Kulturel-Konak,et al.  A review of clonal selection algorithm and its applications , 2011, Artificial Intelligence Review.

[23]  Ajith Abraham,et al.  Intelligent Systems - A Modern Approach , 2011, Intelligent Systems Reference Library.

[24]  Dexuan Zou,et al.  An improved differential evolution algorithm for the task assignment problem , 2011, Eng. Appl. Artif. Intell..

[25]  Ruey-Maw Chen,et al.  Application of Discrete Particle Swarm Optimization for Grid Task Scheduling Problem , 2011 .

[26]  Fernando Niño,et al.  Recent Advances in Artificial Immune Systems: Models and Applications , 2011, Appl. Soft Comput..

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

[28]  Albert Mo Kim Cheng,et al.  Assigning real-time tasks to heterogeneous processors by applying ant colony optimization , 2011, J. Parallel Distributed Comput..

[29]  Goran Martinović,et al.  Elitist Ant System with 2-opt Local Search for the Traveling Salesman Problem , 2012 .

[30]  Alain Billionnet,et al.  An efficient compact quadratic convex reformulation for general integer quadratic programs , 2013, Comput. Optim. Appl..

[31]  Celso A. A. Kaestner,et al.  Particle Swarm Optimization Applied To Task Assignment Problem , 2016 .