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

Authors: 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

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: 10.1504/IJISTA.2017.084218

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

Available online: 13 May 2017 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article