New Reward-Based Movement to Improve Globally-Evolved BCO in Nurse Rostering Problem

Nurse Rostering Problem (NRP) is a crucial problem in hospital industry with combinatorial complex problem. NRP is one of the NP-Hard problems, which means that today there is no definite algorithm that is capable of solving the problem. In this paper, a metaheuristic approach called Reward-Based Movement for Bee Colony Optimization (RBMBCO) is proposed to solve the NRP. It is evaluated using an NRP instance of 30 nurses for 4 weeks of assignment from The Second International Nurse Rostering Competition (INRC-II) dataset. The experimental results show that RBMBCO is capable of generating a better solution than the standard Globally-Evolved Bee Colony Optimization.

[1]  Ying Lin,et al.  An Ant Colony Optimization Approach for Nurse Rostering Problem , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[2]  Suyanto,et al.  Globally Evolved Dynamic Bee Colony Optimization , 2011, KES.

[3]  Ibrahim Almarashdeh,et al.  Hybrid Elitist-Ant System for Nurse-Rostering Problem , 2019, J. King Saud Univ. Comput. Inf. Sci..

[4]  Taïeb Mellouli,et al.  Future Demand Uncertainty In Personnel Scheduling: Investigating Deterministic Lookahead Policies Using Optimization And Simulation , 2016, ECMS.

[5]  Sara Ceschia,et al.  Second International Nurse Rostering Competition (INRC-II) - Problem Description and Rules - , 2015, ArXiv.

[6]  Zhaoquan Cai,et al.  An hybrid evolutionary algorithm with scout bee global search strategy for Chinese nurse rostering problems , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

[7]  J. Amudhavel,et al.  Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem , 2017, Comput. Intell. Neurosci..

[8]  Tai-Hsi Wu,et al.  A particle swarm optimization approach with refinement procedure for nurse rostering problem , 2015, Comput. Oper. Res..

[9]  Warih Maharani,et al.  Isolated Word Recognition Using Ergodic Hidden Markov Models and Genetic Algorithm , 2012 .

[10]  Suyanto,et al.  Optimizing Parameters of Automatic Speech Segmentation into Syllable Units , 2019, International Journal of Intelligent Systems and Applications.

[11]  Peter I. Cowling,et al.  A Memetic Approach to the Nurse Rostering Problem , 2001, Applied Intelligence.

[12]  Suyanto.  An Informed Genetic Algorithm for University Course and Student Timetabling Problems , 2010, ICAISC.

[13]  Sanja Petrovic,et al.  Bee Colony Optimization Algorithm for Nurse Rostering , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[14]  Celia A. Glass,et al.  The nurse rostering problem: A critical appraisal of the problem structure , 2010, Eur. J. Oper. Res..

[15]  Andreas T. Ernst,et al.  An integer programming based ant colony optimisation method for nurse rostering , 2017, 2017 Federated Conference on Computer Science and Information Systems (FedCSIS).

[16]  John Levine,et al.  A hybrid integer and constraint programming approach to solve nurse rostering problems , 2017, Comput. Oper. Res..