• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.216-217
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• 2011

The problem of automated stacking cranes (ASC) dispatching in container terminals is addressed in this paper. We propose a heuristic-based ASC dispatching approach which adopts multi-criteria decision strategy. By aggregating different criteria the proposed strategy can consider multiple aspects of the dispatching situation and make robust decision in various situations. A multi-objective evolutionary algorithm (MOEA) is adopted to tune the weights associated to each criteria to minimize both the quay crane delay and external truck delay. The proposed approach is validated by comparison with different dispatching heuristics and simulation results obtained confirms its effectiveness.

• Journal of Navigation and Port Research
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• v.36 no.5
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• pp.387-394
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• 2012

In an automated container terminal, automated stacking cranes(ASCs) take charge of handling of containers in a block of the stacking yard. This paper proposes a multi-criteria strategy to solve the problem of job dispatching of twin ASCs which are identical to each another in size and specification. To consider terminal situation from different angles, the proposed method evaluates candidate jobs through various factors and it dispatches the best score job to a crane by doing a weighted sum of the evaluated values. In this paper, we derive the criteria for job dispatching strategy, and we propose a genetic algorithm to optimize weights for aggregating evaluated results. Experimental results are shown that it is suitable for real time terminal with lower computational cost and the strategy using various criteria improves the efficiency of the container terminal.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1106-1110
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• 2010

This paper proposes a method of optimizing a stacking strategy for an automated container terminal using multi-objective evolutionary algorithms (MOEAs). Since the yard productivities of seaside and landside are conflicting objectives to be optimized, it is impossible to maximize them simultaneously. Therefore, we derive a Pareto optimal set instead of a single best solution using an MOEA. Preliminary experiments showed that the population is frequently stuck in local optima because of the difficulty of the given problem depending on the yard occupancy rate. To cope with this problem, we propose another method of simultaneously optimizing two problems with different difficulties so that diverse solutions can be preserved in the population. Experimental results showed the proposed method can derive better stacking policies than the compared method solving a single problem given the same computational costs.

• Journal of Navigation and Port Research
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• v.38 no.2
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• pp.155-162
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• 2014

In container terminals, stacking yard is the place where import and export containers are temporarily stored before being loaded onto or after being discharged from a ship. Since all the containers go through the stacking yard in their logistic flow, the productivity of the terminal critically depends on efficient operation of stacking yard, which again depends on how well the stacking locations of the incoming containers are determined. However, a good location for stacking an incoming container later can turn out to be a bad one when that container is to be fetched out of the stacking yard, especially if some rehandling is required. This means that good locations for the containers are changing over time. Therefore, in most container terminals, the so-called remarshaling is done to move the containers from bad location to good locations. Although there are many previous works on remarshaling, they all assume that the remarshaling can be done separately from the main jobs when the cranes are idle for rather a long period of time. However, in reality, cranes are hardly available for a period long enough for remarshaling. This paper proposes a crane dispatching strategy that allows remarshaling jobs to be mixed together with the main jobs whenever an opportunity is detected. Experimental results by simulation reveals that the proposed method effectively contributes to the improvement of terminal productivity.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.359-367
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• 2005

In order to increase the productivity of container terminals, automation is being considered seriously in nowadays. A yard is usually automated by running autumated RMGs (rail mounted gantries) which may require somewhat a different stacking strategy to archive a better performance. In this paper, we present a simulation model for RMGs and summarize experimental results with two different stacking strategies applied to a horizontal block which has two non-crossable RMGs. The concentrating strategy, which stacks containers belong to a single ship together and dedicateds each RMG to either ship services or external truck services, showed a good performance in ship unloading. In the contrast, the distributing strategy, which partitions a block into two regions and binds each RMG to one of the regions to improve the productivity of ship services by running each RMG alternately, is suggested for blocks of exporting.

• Structural Engineering and Mechanics
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• v.25 no.2
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• pp.239-268
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• 2007

This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

• Korean Institute of Interior Design Journal
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• v.13 no.3
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• pp.145-152
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• 2004

The European architects including MVRDV, Rem Koolhaas, Van Berkel, and Zaha Hadid tend to use the their own design strategy based on the objective data. This Architectural design method leads to make new paradigm of contemporary architecture. For the purpose of the understanding a part of new architecture paradigm I will analyze the case of Villa VPRO designed by MVRDV. At the result, I can draw the following conclusions. First, through collecting and analyzing data, drawing design concept and planning the space program, they decided on the design strategies of Villa VPRO. They designed the space volume having 42.4m$\times$42.4m floors and infiltrated environmental elements to solve the problems about deep space. Second, Villa VPRO was constructed by 'creative space-making system: a series of floors much like a geological formation, the continuous floors interconnected by spatial means, the precision bombardments of snake-like holes, open elevations, the stacking spaces. Third, Villa VPRO produced the spectacle space effect the various formation of continuous floors make a lot of difference space types in this building. Also they lead to move naturally and give event space. A numbers of holes and openness make it possible to provide friendly environment with combining light and air with views of the surrounding and transparency. And using the method of stacking many types of space make the differences in height.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2690-2695
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• 2007

This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• International Journal of Air-Conditioning and Refrigeration
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• v.16 no.1
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• pp.1-8
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• 2008

Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.63-70
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• 2004

Port operation is largely divided into gate operation, yard operation and berth operation. Operation strategy and optimal resource allocation for three parts are important in the productivity of the port operation.. Especially the resource allocation planning in berth operation needs optimization, because it is directly connected with the processing time in shipping. Berth planning is not independent on recourse allocation but interrelated with yard stacking area allocation. Therefore, we design the optimized module of berth planning and give priority to interrelationship with yard space allocation, while existing studies design independent resource allocation in berth planning. We suggest constraints by mathematical method, and they are related to yard stacking area allocation with existing constraints. Then we look for solutions, use tabu search to optimize them, and design optimized the berth planning module. In the performance test of optimized module design of berth planning, we find that the berth planning with yard stacking area allocation takes less processing time than without yard stacking area allocation.