NDLI: A new approach for solving set covering problem using jumping particle swarm optimization method

Content Provider	Springer Nature Link
Author	Balaji, S. Revathi, N.
Copyright Year	2015
Abstract	The set covering problem (SCP) is a well known classic combinatorial NP-hard problem, having practical application in many fields. To optimize the objective function of the SCP, many heuristic, meta heuristic, greedy and approximation approaches have been proposed in the recent years. In the development of swarm intelligence, the particle swarm optimization is a nature inspired optimization technique for continuous problems and for discrete problems we have the well known discrete particle swarm optimization (DPSO) method. Aiming towards the best solution for discrete problems, we have the recent method called jumping particle swarm optimization (JPSO). In this DPSO the improved solution is based on the particles attraction caused by attractor. In this paper, a new approach based on JPSO is proposed to solve the SCP. The proposed approach works in three phases: for selecting attractor, refining the feasible solution given by the attractor in order to reach the optimality and for removing redundancy in the solution. The proposed approach has been tested on the benchmark instances of SCP and compared with best known methods. Computational results show that it produces high quality solution in very short running times when compared to other algorithms.
Starting Page	503
Ending Page	517
Page Count	15
File Format	PDF
ISSN	15677818
Journal	Natural Computing
Volume Number	15
Issue Number	3
e-ISSN	15729796
Language	English
Publisher	Springer Netherlands
Publisher Date	2015-07-29
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Set covering Swarm optimization NP-hard problems Theory of Computation Evolutionary Biology Processor Architectures Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications

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