Title: Maximum-weighted tree matching problem: a novel discrete invasive weed optimisation algorithm

 

Author: M. Zandieh; E. Shokrollahpour; M. Bagher

 

Addresses:
Management and Accounting Faculty, Department of Industrial Management, Shahid Beheshti University, G.C., Tehran, 0098, Iran
Management and Accounting Faculty, Department of Industrial Management, Shahid Beheshti University, G.C., Tehran, 0098, Iran
Management and Accounting Faculty, Department of Industrial Management, Shahid Beheshti University, G.C., Tehran, 0098, Iran

 

Journal: Int. J. of Intelligent Systems Technologies and Applications, 2017 Vol.16, No.2, pp.95 - 105

 

Abstract: This paper attempts to solve maximum-weighted tree matching problem (MWTMP). In this type of assignment problem, there are k different tasks to be accomplished and a number of workers/groups. Any worker/group can do any job, with some given profit. The problem is to assign the jobs to workers/groups with the aim of maximising the profit of assignments. This paper presents a novel discrete population-based algorithm, discrete invasive weed optimisation (DIWO) to solve MWTMP. This algorithm is a stochastic numerical algorithm and inspired by weed colonisation trying to find suitable place for growth and reproduction. The performance of the proposed method is examined over benchmarks from the literature and compared to the best algorithm introduced before. Computational results demonstrate the efficiency and robustness of DIWO.

 

Keywords: assignment problem; invasive weed optimisation; MWTMP; maximum-weighted tree matching problem.

 

DOI: http://dx.doi.org/10.1504/IJISTA.2017.10005100

 

Available online 13 May 2017

 

 

Editors Full Text AccessAccess for SubscribersPurchase this articleComment on this article