Erratum: A hybrid genetic algorithmic approach to the maximally diverse grouping problem

Corrections to: Journal of the Operational Research Society (2010). doi:10.1057/jors.2009.168; published online 6 January 2010The maximally diverse grouping problem (MDGP) is a NP-complete problem. For such NP-complete problems, heuristics play a major role in searching for solutions. Most of the heuristics for MDGP focus on the equal group-size situation. In this paper, we develop a genetic algorithm (GA)-based hybrid heuristic to solve this problem considering not only the equal group-size situation but also the different group-size situation. The performance of the algorithm is compared with the established Lotfi–Cerveny–Weitz algorithm and the non-hybrid GA. Computational experience indicates that the proposed GA-based hybrid algorithm is a good tool for solving MDGP. Moreover, it can be easily modified to solve other equivalent problems.

[1]  Jan Karel Lenstra,et al.  A local search template , 1998, Comput. Oper. Res..

[2]  R. R. Weitz,et al.  An empirical comparison of heuristic methods for creating maximally diverse groups , 1998, J. Oper. Res. Soc..

[3]  Michael J. Pazzani,et al.  Mining for proposal reviewers: lessons learned at the national science foundation , 2006, KDD '06.

[4]  Zahra Naji Azimi,et al.  Hybrid heuristics for Examination Timetabling problem , 2005, Appl. Math. Comput..

[5]  Mihalis Yannakakis,et al.  The Analysis of Local Search Problems and Their Heuristics , 1990, STACS.

[6]  Vahid Lotfi,et al.  A Final-Exam-Scheduling Package , 1991 .

[7]  Guoyong Shi,et al.  A genetic algorithm applied to a classic job-shop scheduling problem , 1997, Int. J. Syst. Sci..

[8]  Thomas A. Feo,et al.  One-Half Approximation Algorithms for the k-Partition Problem , 1992, Oper. Res..

[9]  Anshul Mittal,et al.  A GENETIC ALGORITHM , 2010 .

[10]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[11]  F. J. Vasko,et al.  An empirical study of hybrid genetic algorithms for the set covering problem , 2005, J. Oper. Res. Soc..

[12]  John M. Wilson,et al.  A genetic algorithm for flow shop scheduling problems , 2004, J. Oper. Res. Soc..

[13]  John A. Miller,et al.  An evaluation of local improvement operators for genetic algorithms , 1993, IEEE Trans. Syst. Man Cybern..

[14]  J. David Schaffer,et al.  Proceedings of the third international conference on Genetic algorithms , 1989 .

[15]  Hsiao-Fan Wang,et al.  Modeling and analysis for multi-period, multi-product and multi-resource production scheduling , 2003, J. Intell. Manuf..

[16]  Hsiao-Fan Wang,et al.  Hybrid genetic algorithm for optimization problems with permutation property , 2004, Comput. Oper. Res..

[17]  Juan Julián Merelo Guervós,et al.  Parallel Problem Solving from Nature - PPSN IX: 9th International Conference, Reykjavik, Iceland, September 9-13, 2006, Proceedings , 2006, PPSN.

[18]  Lawrence Davis,et al.  Job Shop Scheduling with Genetic Algorithms , 1985, ICGA.

[19]  R. R. Weitz,et al.  On a Heuristic for the Final Exam Scheduling Problem , 1996 .

[20]  Yves Crama,et al.  Local Search in Combinatorial Optimization , 2018, Artificial Neural Networks.

[21]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[22]  Martina Gorges-Schleuter,et al.  ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy , 1989, ICGA.

[23]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[24]  Joyendu Bhadury,et al.  Maximizing Workforce Diversity In Project Teams: A Network Flow Approach. , 2000 .

[25]  Rob R. Weitz,et al.  Assigning Students to Groups: A Multi‐Criteria Decision Support System Approach* , 1992 .

[26]  Barrie M. Baker,et al.  Assigning pupils to tutor groups in a comprehensive school , 2001, J. Oper. Res. Soc..

[27]  G. Croes.  A Method for Solving Traveling-Salesman Problems , 1958 .

[28]  Thomas A. Feo,et al.  A class of bounded approximation algorithms for graph partitioning , 1990, Networks.

[29]  L. D. Whitley,et al.  The Traveling Salesman and Sequence Scheduling : , 1990 .

[30]  Mitsuo Gen,et al.  Genetic algorithms and engineering design , 1997 .

[31]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[32]  Stephen G. Powell,et al.  Methods for assigning students to groups: a study of alternative objective functions , 2002, J. Oper. Res. Soc..

[33]  J. K. Lenstra,et al.  Local Search in Combinatorial Optimisation. , 1997 .

[34]  V. Lotfi,et al.  A Three Phased Approach To Final Exam Scheduling , 1989 .