Wisdom of Artificial Crowds-A Metaheuristic Algorithm for Optimization

Yampolskiy, Roman V.; Ashby, Leif; Hassan, Lucas
May 2012
Journal of Intelligent Learning Systems & Applications;May2012, Vol. 4 Issue 2, p98
Academic Journal
Finding optimal solutions to NP-Hard problems requires exponential time with respect to the size of the problem. Consequently, heuristic methods are usually utilized to obtain approximate solutions to problems of such difficulty. In this paper, a novel swarm-based nature-inspired metaheuristic algorithm for optimization is proposed. Inspired by human collective intelligence, Wisdom of Artificial Crowds (WoAC) algorithm relies on a group of simulated intelligent agents to arrive at independent solutions aggregated to produce a solution which in many cases is superior to individual solutions of all participating agents. We illustrate superior performance of WoAC by comparing it against another bio-inspired approach, the Genetic Algorithm, on one of the classical NP-Hard problems, the Travelling Salesperson Problem. On average a 3% - 10% improvement in quality of solutions is observed with little computational overhead.


Related Articles

  • Computation of the travelling salesman problem by a shrinking blob. Jones, Jeff; Adamatzky, Andrew // Natural Computing;Mar2014, Vol. 13 Issue 1, p1 

    The travelling salesman problem (TSP) is a well known and challenging combinatorial optimisation problem. Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, candidate solutions. Some methods take their inspiration from...

  • Performance Assessment over Heuristic Population Seeding Techniques of Genetic Algorithm: Benchmark Analyses on Traveling Salesman Problems. Shanmugam, M.; Saleem Basha, M. S.; Paul, P. Victer; Dhavachelvan, P.; Baskaran, R. // International Journal of Applied Engineering Research;2013, Vol. 8 Issue 10, p1171 

    Traveling Salesman Problem (TSP) is most widely studied combinational optimization problem and Genetic Algorithm (GA) is a familiar meta-heuristic search technique applied to find the optimal solution for the complex problem effectively. In GA, the quality of solutions in population...

  • Developing Improved Greedy Crossover to Solve Symmetric Traveling Salesman Problem. Ismkhan (Esmkhan), Hassan; Zamanifar, Kamran // International Journal of Computer Science Issues (IJCSI);Jul2012, Vol. 9 Issue 4, p121 

    The Traveling Salesman Problem (TSP) is one of the most famous optimization problems. Greedy crossover designed by Greffenstette et al, can be used while Symmetric TSP (STSP) is resolved by Genetic Algorithm (GA). Researchers have proposed several versions of greedy crossover. Here we propose...

  • Genetic Algorithm Performance with Different Selection Strategies in Solving TSP. Razali, Noraini Mohd; Geraghty, John // Proceedings of the World Congress on Engineering 2011 Volume I;2011, p156 

    A genetic algorithm (GA) has several genetic operators that can be modified to improve the performance of particular implementations. These operators include parent selection, crossover and mutation. Selection is one of the important operations in the GA process. There are several ways for...

  • Open Vehicle Routing Problem by Ant Colony Optimization. GurpreetSingh; Dhir, Vijay // International Journal of Advanced Computer Science & Application;2014, Vol. 5 Issue 3, p63 

    Vehicle routing problem (VRP) is real-world combinatorial optimization problem which determine the optimal route of a vehicle. Generally, to provide the efficient vehicle serving to the customer through different services by visiting the number of cities or stops, the VRP follows the Travelling...

  • Velocity Tentative PSO: An Optimal Velocity Implementation based Particle Swarm Optimization to Solve Traveling Salesman Problem. Akhand, M. A. H.; Akter, Shahina; Rashid, M. A.; Yaakob, S. B. // IAENG International Journal of Computer Science;Sep2015, Vol. 42 Issue 3, p221 

    This paper introduces an effective Particle Swarm Optimization (PSO) based algorithm for solving Traveling Salesman Problem (TSP). Among prominent PSO based methods, the proposed Velocity Tentative PSO (VTPSO) considers Swap Sequence (SS) for velocity operation of the particles. A velocity SS is...

  • ISPO: A New Way to Solve Traveling Salesman Problem. Xiaohua Wang; Aiqin Mu; Shisong Zhu // Intelligent Control & Automation (2153-0653);May2013, Vol. 4 Issue 2, p122 

    This paper first introduces the concepts of mobile operators and mobile sequence, with which it redefines the rate of particle swarm optimization algorithm and the formula of position updating. Combining this discrete PSO algorithm with neighbors, the paper puts forward Hybrd Particle Swarm...

  • An Improved Modular Hybrid Ant Colony Approach for Solving Traveling Salesman Problem. Sahana, Sudip Kumar; Jain, Aruna // GSTF Journal on Computing;2011, Vol. 1 Issue 2, p123 

    Our primary aim is to design a framework to solve the well known traveling salesman problem(TSP) using combined approach of Ant Colony Optimization (ACO) and Genetic Algorithm (GA). Several solutions exists for the above problem using ACO or GA and even using a hybrid approach of ACO and GA. Our...

  • Fast Algorithms for Geometric Traveling Salesman Problems. Bentley, Jon Jouis // ORSA Journal on Computing;Fall92, Vol. 4 Issue 4, p387 

    This paper describes efficient algorithms for computing approximate traveling salesman tours in multidimensional point sets. We describe implementations of a dozen starting heuristics (including Nearest Neighbor and Farthest Insertion) and three local optimizations (including 2-Opt and 3-Opt)....


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics