A memetic algorithm for the quadratic multiple container packing problem

In this paper, we propose a new memetic algorithm for the quadratic multiple container packing problem. The proposed memetic algorithm is based on the adaptive link adjustment evolutionary algorithm (ALA-EA) and it incorporates heuristic fitness improvement schemes into the ALA-EA. In addition, we propose a new powerful initialization method for the QMCPP.The proposed algorithm is compared to the previous approaches. We report that it can find much improved final solutions at most benchmark instances. Moreover, even the best solutions of the first generation show better than the previous known best solutions at most of instances especially with density d=0.75.In addition, we compare the proposed memetic algorithm to the NetKey based evolutionary algorithm for analyzing features of the ALA-EA.

[1]  Tugba Saraç,et al.  A Genetic Algorithm for the Quadratic Multiple Knapsack Problem , 2007, BVAI.

[2]  James C. Bean,et al.  Genetic Algorithms and Random Keys for Sequencing and Optimization , 1994, INFORMS J. Comput..

[3]  Bryant A. Julstrom.  Comparing Darwinian, Baldwinian, and Lamarckian Search in a Genetic Algorithm for the 4-Cycle Proble , 1999 .

[4]  Alfonsas Misevicius,et al.  An improved hybrid genetic algorithm: new results for the quadratic assignment problem , 2004, Knowl. Based Syst..

[5]  Alok Singh,et al.  A New Grouping Genetic Algorithm for the Quadratic Multiple Knapsack Problem , 2007, EvoCOP.

[6]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[7]  David W. Corne,et al.  A New Evolutionary Algorithm for Spanning-Tree Based Communication Network Design , 2005, IEICE Trans. Commun..

[8]  Franz Rothlauf,et al.  Network Random KeysA Tree Representation Scheme for Genetic and Evolutionary Algorithms , 2002, Evolutionary Computation.

[9]  Sang-Moon Soak,et al.  'Adaptive Link Adjustment' Applied to the Fixed Charge Transportation Problem , 2007, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[10]  L. D. Whitley,et al.  The No Free Lunch and problem description length , 2001 .

[11]  Yongming Li,et al.  Multi-population co-genetic algorithm with double chain-like agents structure for parallel global numerical optimization , 2010, Applied Intelligence.

[12]  L. Darrell Whitley,et al.  Adding Learning to the Cellular Development of Neural Networks: Evolution and the Baldwin Effect , 1993, Evolutionary Computation.

[13]  Ashish Tiwari,et al.  A greedy genetic algorithm for the quadratic assignment problem , 2000, Comput. Oper. Res..

[14]  David W. Corne,et al.  A New Encoding for the Degree Constrained Minimum Spanning Tree Problem , 2004, KES.

[15]  John E. Beasley,et al.  A Genetic Algorithm for the Multidimensional Knapsack Problem , 1998, J. Heuristics.

[16]  Gi-Tae Yeo,et al.  An effective evolutionary algorithm for the multiple container packing problem , 2008 .

[17]  Steven Orla Kimbrough,et al.  On a Feasible-Infeasible Two-Population (FI-2Pop) genetic algorithm for constrained optimization: Distance tracing and no free lunch , 2008, Eur. J. Oper. Res..

[18]  George Papageorgiou,et al.  A Connectionist Approach for Solving Large Constraint Satisfaction Problems , 1997, Applied Intelligence.

[19]  Alfonsas Misevicius.  Genetic algorithm hybridized with ruin and recreate procedure: application to the quadratic assignment problem , 2003, Knowl. Based Syst..

[20]  Sang-Wook Lee,et al.  The improved adaptive link adjustment evolutionary algorithm for the multiple container packing problem , 2008, Applied Intelligence.

[21]  Günther R. Raidl,et al.  Genetic Algorithms for the Multiple Container Packing Problem , 1998, PPSN.

[22]  J. Kruskal.  On the shortest spanning subtree of a graph and the traveling salesman problem , 1956 .

[23]  Franz Rothlauf,et al.  Network random keys-a tree network representation scheme for genetic and evolutionary algorithms , 2000 .

[24]  Franz Rothlauf,et al.  Evolution Strategies, Network Random Keys, and the One-Max Tree Problem , 2002, EvoWorkshops.

[25]  Alok Singh,et al.  A hybrid heuristic for the maximum clique problem , 2006, J. Heuristics.

[26]  Bryant A. Julstrom,et al.  The quadratic multiple knapsack problem and three heuristic approaches to it , 2006, GECCO.

[27]  Andrew Lim,et al.  3-D Container Packing Heuristics , 2005, Applied Intelligence.

[28]  Haesun Park,et al.  Statistical properties analysis of real world tournament selection in genetic algorithms , 2008, Applied Intelligence.

[29]  L. Darrell Whitley,et al.  A Hybrid Genetic Algorithm for the Quadratic Assignment Problem , 2000, GECCO.

[30]  L. Darrell Whitley,et al.  Lamarckian Evolution, The Baldwin Effect and Function Optimization , 1994, PPSN.

[31]  B. John Oommen,et al.  Optimal sampling for estimation with constrained resources using a learning automaton-based solution for the nonlinear fractional knapsack problem , 2010, Applied Intelligence.