(CONTAINER STOWAGE PLANNING (CSP
اسلاید 1: By:Maasoomeh KarimiFall 2008CONTAINER STOWAGE PLANNING (CSP)In the name of God
اسلاید 2: contentAn introduction to Container Stowage planningSome definitionsProblem importanceProblem complexityModels and solution techniquesCase studyReference 2
اسلاید 3: Some definitions3(Anna Sciomachen , Elena Tanfani, )
اسلاید 4: problem importanceContainerization has increasingly facilitated the transportation of cargo since the 1970s (I.D. Wilson, P.A. Roach, J.A. Ware, 2001).The standard frame and dimentions of containers allows containerized cargo to be transported by rail, truck or sea (I.D. Wilson, P.A. Roach, J.A. Ware, 2001).The fast ship turnaround at a container terminal is essential for the economic performance of shipping companies (Akio Imai, Kazuya Sasaki, Etsuko Nishimura, Stratos Papadimitriou, 2006).4
اسلاید 5: problem importance (cont’d)The turnaround time of a ship includes the time for berthing, unloading, loading and departure (Akio Imai, Kazuya Sasaki, Etsuko Nishimura, Stratos Papadimitriou, 2006).Determining a viable arrangement of containers that facilitates loading and unloading process, in a cost-effective way, makes up the container stowage problem (I.D. Wilson, P.A. Roach, J.A. Ware, 2001).5
اسلاید 6: Problem complexity6
اسلاید 7: The structure of container ship (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)7In particular, each location is addressed by the following indices:
اسلاید 8: The structure of container ship (cont’d)8Numbering of tiersNumbering of rowsNumbering of bays (I.D. WILSON AND P.A. ROACH, 1999)
اسلاید 9: The structure of container ship (cont’d)9
اسلاید 10: The constraints of the problem (Anna Sciomachen, Elena Tanfani, 2007; Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)10
اسلاید 11: Size of container constraints (Anna Sciomachen, Elena Tanfani, 2007)Constraints related to 40 feet containersConstraints related to 20 feet containers 11
اسلاید 12: Type of container constraints (I.D. Wilson, P.A. Roach, J.A. Ware, 2001; Anna Sciomachen, Elena Tanfani, 2007)Reefer containers‘Out of gauge’ containersEmpty and open top containersFantainersHazardous containers12
اسلاید 13: Weight constraints (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, )The total weight of all containers cannot exceed the maximum weight capacity.the weight of a stack of three containers of 20 feet and 40 feet cannot be greater than an a priori established value.the weight of a container located in a tier cannot be greater than the weight of the container located in a lower tier having the same row and bay.13
اسلاید 14: Operational and security constraints: (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004; Anna Sciomachen, Elena Tanfani, 2007)Cross equilibrium (Q1)Horizontal equilibrium (Q2)Vertical equilibrium (Q3)14
اسلاید 15: Destination constraints: (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004) Loading first those containers having as destination the final stop of the ship and consequently load last those containers that have to be unloaded first.15
اسلاید 16: Objective function classification (Akio Imai, Kazuya Sasaki, Etsuko Nishimura, Stratos Papadimitriou, 2006; Anna Sciomachen, Elena Tanfani, 2007)16
اسلاید 17: Models classification17
اسلاید 18: A 0-1 Linear programming model (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004) Formally, the master bay plan problem (MBPP) involves determining how to stow a set C of m containers of different types into a set S of n available locations within a containership, with respect to some structural and operational constraints related to both the containers and the ship, whilst minimising the total stowage time (see, e.g., Ambrosino and Sciomachen, 1998).18
اسلاید 19: A 0-1 Linear programming model (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)19(1)(2)(3)(4)(5)(6)(7)
اسلاید 20: A 0-1 Linear programming model (cont’d) (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)20(8)(9)(10)(11)(12)(13)
اسلاید 21: A 0-1 Linear programming model (cont’d) (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)21(14)(15)(16)(17)(18)
اسلاید 22: A model divided into sub-problems (I.D. Wilson, P.A. Roach, J.A. Ware, 2001)underlying heuristics used to generate stowage solution and their subsequent evaluation.Decomposing the planning process into two sub-process:A strategic planning processSolution technique: branch and bound searchA tactical planning processSolution technique: Tabu search22
اسلاید 23: A multi-objective integer programming (Akio Imai, Kazuya Sasaki, Etsuko Nishimura, Stratos Papadimitriou, 2006)relationship between ship stability and the loading-related rehandleEmploying the weighting method (Cohon, 1978)Objective function: maximization of the ship atability, minimization of the loading related rehandleSolution technique: Genetic algorithm23
اسلاید 24: Solution techniques (I.D. Wilson, P.A. Roach, J.A. Ware, 2001; Akio Imai, Kazuya Sasaki, Etsuko Nishimura, Stratos Papadimitriou, 2006; Anna Sciomachen, Elena Tanfani, 2007 )
اسلاید 25: Case study (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)the Chiwaua containership, that is a ‘‘client’’ of the maritime terminal in Genoa (Italy)It is a 198 TEU containership, with 11 bays, four rows and five tiers (three in the hold and two in the upper deck, respectively)Testing the approach deducing the master bay plan by referring to 13 cases, reported in Table 1.25
اسلاید 26: Case study (cont’d) (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004) The impact of the destination constraints (15) in the cases 9 and 11, computational time reduces respectively from 103 to 22 min in the relaxed model, and from 112 to 35 min on the same platform.Manually compiling the corresponding master bay plans takes about from 60 to 90 min26
اسلاید 27: Case study (cont’d) (Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004)Achievement 26 container movements/hour, versus the same index in the present operational scenario at the maritime terminal that is about 24.28,500 variables for case 1 up to 45,030 for case13from 14,015 to 18,231 constraints for the same cases27
اسلاید 28: Refrence Anna Sciomachen, Elena Tanfani, 2007. A 3D-BPP approach for optimising stowage plans and terminal productivity. European Journal of Operational Research 183, 1433–1446.Akio Imai, Kazuya Sasaki, Etsuko Nishimura, Stratos Papadimitriou, 2006. Multi-objective simultaneous stowage and load planning for a container ship with container rehandle in yard stacks. European Journal of Operational Research 171, 373–389.Daniela Ambrosino, Anna Sciomachen, Elena Tanfani, 2004. Stowing a containership: the master bay plan problem. Transportation Research Part A 38, 81–99.Wilson, I.D., Roach, P.A., Ware, J.A., 2001. Container stowage pre-planning: Using search to generate solutions, a case study. Knowledge-Based Systems 14, 137–145.Wilson, I.D., Roach, P.A., 1999. Principles of combinatorial optimization applied to container-ship stowage planning. Journal of Heuristics 5, 403–418.28
اسلاید 29: Thanks for your attention!29
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