Mozhgan Azarkish
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Mozhgan Azarkish has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Azar Sadeghnejad-Barkousaraie
University of Tehran
4 shared publications - Reza Tavakkoli-Moghaddam
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
4 shared publications P Shahnazari-Shahrezaei
Islamic Azad University
1 shared publication
Latest Publications
- Open Access
- 3 December 2012
- Published by Stellenbosch University in South African Journal of Industrial Engineering
- Vol. 23 (3) , 68
A DIFFERENTIAL EVOLUTION ALGORITHM DEVELOPED FOR A NURSE SCHEDULING PROBLEM
Nurse scheduling is a type of manpower allocation problem that tries to satisfy hospital managers objectives and nurses preferences as much as possible by generating fair shift schedules. This paper presents a nurse scheduling problem based on a real case study, and proposes two meta-heuristics a differential evolution algorithm (DE) and a greedy randomised adaptive search procedure (GRASP) to solve it. To investigate the efficiency of the proposed algorithms, two problems are solved. Furthermore, some comparison metrics are applied to examine the reliability of the proposed algorithms. The computational results in this paper show that the proposed DE outperforms the GRASP
- 3 December 2012
- Published by Stellenbosch University in South African Journal of Industrial Engineering
- Vol. 23 (3) , 68
Open AccessA DIFFERENTIAL EVOLUTION ALGORITHM DEVELOPED FOR A NURSE SCHEDULING PROBLEM
Nurse scheduling is a type of manpower allocation problem that tries to satisfy hospital managers objectives and nurses preferences as much as possible by generating fair shift schedules. This paper presents a nurse scheduling problem based on a real case study, and proposes two meta-heuristics a differential evolution algorithm (DE) and a greedy randomised adaptive search procedure (GRASP) to solve it. To investigate the efficiency of the proposed algorithms, two problems are solved. Furthermore, some comparison metrics are applied to examine the reliability of the proposed algorithms. The computational results in this paper show that the proposed DE outperforms the GRASP
- 1 September 2011
- Published by Elsevier in Expert Systems with Applications
- Vol. 38 (9) , 10812-10821
A new hybrid multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem
- 1 September 2011
- Published by Elsevier in Expert Systems with Applications
- Vol. 38 (9) , 10812-10821
A new hybrid multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem