Multiobjective Approaches for the Ship Stowage Planning Problem Considering Ship Stability and Container Rehandles

The ship stowage planning problem (SSPP) is a very complex and challenging problem in the logistics industries because it affects the benefits of both shipping lines and port terminals. In this paper, we investigate a multiobjective SSPP, which aims to optimize the ship stability and the number of rehandles simultaneously. We use metacentric height, list value, and trim value to measure the ship stability. Meanwhile, the number of rehandles is the sum of rehandles by yard cranes and quay cranes and all necessary rehandles at future ports. To solve this problem, a variant of the nondominated sorting genetic algorithm III (NSGA-III) combined with a local search component is proposed. The algorithm can produce a set of nondominated solutions. Decision makers can then choose the most promising solution for practical implementation based on their experience and preferences. Extensive experiments are carried out on two groups of instances. The computational results demonstrate the effectiveness of the proposed algorithm compared to the NSGA-II and random weighted genetic algorithms, especially when it is applied in solving the six-objective SSPP.

[1]  Akio Imai,et al.  Multi-objective simultaneous stowage and load planning for a container ship with container rehandle in yard stacks , 2006, Eur. J. Oper. Res..

[2]  Stefan Voß,et al.  Operations research at container terminals: a literature update , 2007, OR Spectr..

[3]  Alberto Delgado,et al.  A Constraint Programming model for fast optimal stowage of container vessel bays , 2012, Eur. J. Oper. Res..

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

[5]  David E. Goldberg,et al.  Genetic Algorithms, Tournament Selection, and the Effects of Noise , 1995, Complex Syst..

[6]  Alberto Delgado,et al.  Fast Generation of Near-Optimal Plans for Eco-Efficient Stowage of Large Container Vessels , 2011, ICCL.

[7]  Stefan Voß,et al.  Container terminal operation and operations research - a classification and literature review , 2004, OR Spectr..

[8]  Anna Sciomachen,et al.  A new three-step heuristic for the Master Bay Plan Problem , 2009 .

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

[10]  Paul A. Roach,et al.  Principles of Combinatorial Optimization Applied to Container-Ship Stowage Planning , 1999, J. Heuristics.

[11]  Andrew Lim,et al.  Iterative Deepening A* Algorithms for the Container Relocation Problem , 2012, IEEE Transactions on Automation Science and Engineering.

[12]  Wen-Jing Hsu,et al.  Improving Safety and Stability of Large Containerships in Automated Stowage Planning , 2011, IEEE Systems Journal.

[13]  J.-G. Kang,et al.  Stowage planning in maritime container transportation , 2002, J. Oper. Res. Soc..

[14]  I. D. Wilson,et al.  Container stowage planning: a methodology for generating computerised solutions , 2000, J. Oper. Res. Soc..

[15]  Marco Laumanns,et al.  Performance assessment of multiobjective optimizers: an analysis and review , 2003, IEEE Trans. Evol. Comput..

[16]  Carlos A. Coello Coello,et al.  Solving Multiobjective Optimization Problems Using an Artificial Immune System , 2005, Genetic Programming and Evolvable Machines.

[17]  Pablo Moscato,et al.  A Gentle Introduction to Memetic Algorithms , 2003, Handbook of Metaheuristics.

[18]  V L Belenky,et al.  Stability and Safety of Ships: Risk of Capsizing , 2007 .

[19]  Anna Sciomachen,et al.  An Experimental Comparison of Different Heuristics for the Master Bay Plan Problem , 2010, SEA.

[20]  Kalyanmoy Deb,et al.  An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.

[21]  Feng Li,et al.  An Integer Linear Programming for Container Stowage Problem , 2008, ICCS.

[22]  Andreas Bortfeldt,et al.  A tree search procedure for the container pre-marshalling problem , 2012, Eur. J. Oper. Res..

[23]  Stefan Voß,et al.  A mathematical formulation and complexity considerations for the blocks relocation problem , 2012, Eur. J. Oper. Res..

[24]  Anna Sciomachen,et al.  Stowing a containership: the master bay plan problem , 2004 .

[25]  Mordecai Avriel,et al.  Container ship stowage problem: complexity and connection to the coloring of circle graphs , 2000, Discret. Appl. Math..

[26]  A. Sciomachen,et al.  The master bay plan problem: a solution method based on its connection to the three‐dimensional bin packing problem , 2003 .

[27]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[28]  Gregory Levitin,et al.  A Genetic Algorithm with a Compact Solution Encoding for the Container Ship Stowage Problem , 2002, J. Heuristics.

[29]  John E. Dennis,et al.  Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems , 1998, SIAM J. Optim..

[30]  Stefan Voß,et al.  Applying the corridor method to a blocks relocation problem , 2011, OR Spectr..

[31]  Wen-Jing Hsu,et al.  Randomized Algorithm with Tabu Search for Multi-Objective Optimization of Large Containership Stowage Plans , 2011, ICCL.

[32]  Anna Sciomachen,et al.  A decomposition heuristics for the container ship stowage problem , 2006, J. Heuristics.

[33]  Yusin Lee,et al.  An optimization model for the container pre-marshalling problem , 2007, Comput. Oper. Res..

[34]  Mordecai Avriel,et al.  Stowage planning for container ships to reduce the number of shifts , 1998, Ann. Oper. Res..

[35]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[36]  Philip M. Kaminsky,et al.  A Multi-stage Decomposition Heuristic for the Container Stowage Problem , 2008 .

[37]  Garry Robinson,et al.  Ship Stability and Parametric Rolling , 2009 .