A Hybrid Multiobjective Evolutionary Algorithm for the Sailor Assignment Problem

This paper examines a multiobjective formulation of the United States Navy’s Sailor Assignment Problem (SAP) and examines the performance of two widely-used multiobjective evolutionary algorithms (MOEAs) on large instances of this problem. The performance of the algorithms is examined with respect to both solution quality and diversity, and the algorithms are shown to provide inadequate diversity along the Pareto front. A domain-specific local improvement operator is introduced into the MOEAs, producing significant performance increases over the evolutionary algorithms alone. This hybrid MOEA approach is applied to the sailor assignment problem and shown to provide greater diversity along the Pareto front.

[1]  Hisao Ishibuchi,et al.  Multi-objective genetic local search algorithm , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[2]  Lee McCauley,et al.  A large-scale multi-agent system for navy personnel distribution , 2002, Connect. Sci..

[3]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[4]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[5]  Dipankar Dasgupta,et al.  Genetic algorithms for the sailor assignment problem , 2005, GECCO '05.

[6]  Andrzej Jaszkiewicz,et al.  Genetic local search for multi-objective combinatorial optimization , 2022 .

[7]  Charles Fleurent,et al.  Genetic Hybrids for the Quadratic Assignment Problem , 1993, Quadratic Assignment and Related Problems.

[8]  V. Deineko,et al.  The Quadratic Assignment Problem: Theory and Algorithms , 1998 .

[9]  M. Ožana,et al.  Large Scale Crew Rostering , 2003 .

[10]  Pablo Moscato,et al.  Memetic algorithms: a short introduction , 1999 .

[11]  Peter A. N. Bosman,et al.  Exploiting gradient information in numerical multi--objective evolutionary optimization , 2005, GECCO '05.

[12]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[13]  Félix Mora-Camino,et al.  A Bi-Criterion Approach for the Airlines Crew Rostering Problem , 2001, EMO.

[14]  Allen Holder,et al.  Navy Personnel Planning and the Optimal Partition , 2005, Oper. Res..

[15]  Günther R. Raidl,et al.  An improved hybrid genetic algorithm for the generalized assignment problem , 2004, SAC '04.

[16]  Joshua D. Knowles,et al.  M-PAES: a memetic algorithm for multiobjective optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[17]  Bernd Freisleben,et al.  A Genetic Local Search Approach to the Quadratic Assignment Problem , 1997, ICGA.

[18]  Martin Brown,et al.  Effective Use of Directional Information in Multi-objective Evolutionary Computation , 2003, GECCO.

[19]  L. S. Shapley,et al.  College Admissions and the Stability of Marriage , 2013, Am. Math. Mon..

[20]  Jeffery L. Kennington,et al.  Assignment with En route training of navy personnel , 1993, Naval Research Logistics (NRL).

[21]  Mark W. Lewis,et al.  Guided design search in the interval-bounded sailor assignment problem , 2006, Comput. Oper. Res..

[22]  Giorgio Gallo,et al.  A Multicommodity Flow Approach to the Crew Rostering Problem , 2004, Oper. Res..

[23]  Larry J. Eshelman The CHC Adaptive Search Algo-rithm , 1991 .

[24]  Thomas A. Blanco,et al.  A Sea Story: Implementing the Navy's Personnel Assignment System , 1994, Oper. Res..