AI SearchContainer storage allocation with top stackers for an inland container depot
Call Number: AIT Thesis no. ISE-03-12 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. ISE-03-12Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2003Description: 71 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 2003 Summary: This study considers how to allocate storage spaces for import containers with top stackers and automated guided vehicles (AGVs) in an inland container depot (ICD). The performance measure is the rehandling work. The stack height and number of container stacks of each shipment are important decision variables. In the segregation strategy, containers unloaded during different shipment are not allowed to mix with each other. Available locations or spaces are allocated for each shipment for minimizing the expected total number of rehandles to picking up all containers. Genetic algorithm (GA) is a methodology proposed for searching for the good solutions. A computer programming, written in visual basic language, was developed. The GA is compared with Kim's and Lingo method. The result shows that in the larger size of time period planning horizon (T), the GA program give the better result of computational time, while the different result of GA and Lingo is not significant. Comparing GA and Kim's result, GA value is better than Kim's in the larger size of time period planning horizon. The GA program is a suitable method for solving the container allocation problem of a larger size of time period, more than 30 time periods to yield good solutions within a reasonable computational time.
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Thesis (M.Eng.) - Asian Institute of Technology, 2003
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies
This study considers how to allocate storage spaces for import containers with top stackers and automated guided vehicles (AGVs) in an inland container depot (ICD). The performance measure is the rehandling work. The stack height and number of container stacks of each shipment are important decision variables. In the segregation strategy, containers unloaded during different shipment are not allowed to mix with each other. Available locations or spaces are allocated for each shipment for minimizing the expected total number of rehandles to picking up all containers. Genetic algorithm (GA) is a methodology proposed for searching for the good solutions. A computer programming, written in visual basic language, was developed. The GA is compared with Kim's and Lingo method. The result shows that in the larger size of time period planning horizon (T), the GA program give the better result of computational time, while the different result of GA and Lingo is not significant. Comparing GA and Kim's result, GA value is better than Kim's in the larger size of time period planning horizon. The GA program is a suitable method for solving the container allocation problem of a larger size of time period, more than 30 time periods to yield good solutions within a reasonable computational time.
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