• Journal of the Society of Naval Architects of Korea
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• v.45 no.4
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• pp.432-440
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• 2008

Korean shipbuilders are starting to use three dimensional solid CAD systems to enhance their competitiveness in design and production. Despite many merits, three dimensional CAD systems reveal some problems in pipe-line modeling. Pipe-line modeling is heavily dependent on point data in routing. However, since the models built by sweeping or skinning operations do not have data about points and lines on the surfaces, the point data for routing are currently manually calculated by considering the diameters of the pipes and alignment conditions with other pipes. This process is inefficient and prone to errors. In order to enhance the pipe modeling, this paper presents an Offset Routing Program for a three dimensional CAD system, which aids designers to easily define the start points and to generate the pipe routings using reference objects.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.117-129
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• 1998

This study is concerned with developing a heuristic for a web-based vehicle routing problem using mixed genetic algorithm(VRPMGA) which determines each vehicle route in order to minimize the transportation costs, subject to meeting the demands of all delivery points. VRP is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a mixed genetic algorithm by partitioned strategy which can give a good solution in comparatively brief time. The good features of the VRPMGA are, fristly, the ability of early convergence and, secondly, the capability of producing multiple, alternative, and near-optimal solutions. The VRPMGA is a useful algorithm that can be appliable to VRP and TSP. Finally, the computational test were performed using the benchmark problems and the proposed heuristic is compared with the other existing algorithms (COSA). The result of computational tests shows that proposed heuristic gives good solutions, in much shorter time, which are same as the best known solutions in the pervious research.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.389-392
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• 2004

The column generation process for the set-partitioning model of the vehicle routing problem requires repeated solutions of column generation subproblems which has a combinatorial structure similar to that of the traveling salesman problem. This limits the size of the problem that can be addressed. We introduce a new modeling approach, termed route-splitting, which splits each vehicle route into segments, and results in more tractable subproblems. A lower bounding scheme that yields an updated bound at each iteration of the column generation process is developed. Implementation issues, including a technique of controlling columns in the master problem, are explored. Lower bounds are computed on standard benchmark problems with up to 199 customers.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.325-336
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• 1996

This study is concerned with developing a heuristic for the vehicle routing problem(VRP) which determines each vehicle route in order to minimize the transportation costs, subject to meeting the demands of all delivery points. VRP is known 10 be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristic are more frequently developed than optimal algorithms. This study aims to develop a heuristic which can give a good solution in comparatively brief time. Finally, the computational tests were performed using the benchmark problems and the proposed heuristic is compared with the other existing algorithms. The result of computational tests shows that the proposed heuristic gives good solutions, in much shorter time, which are not 1% more expensive than the best known solutions, which are same as the best known solutions in the previous researches.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.10-18
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• 2002

A more comprehensive analytical framework for examining the relative merits of alternative dispatching process policies for nurseries is developed in this paper. The efficiency of the dispatch process of plants in a nursery is analysed using a vehicle routing model. The problem then involves determining in what order each vehicle should visit its locations. The problem is NP-hard. Several heuristic techniques are used to solve a real life nursery sequencing problem. The results obtained by these heuristic techniques are compared with each other and the current sequencing of orders. The model with some minor alterations can be also used to minimise the dispatching and collecting process in different agricultural plants.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.31-47
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• 2007

The main purpose of this study is to find out the best solution of the vehicle routing problem with hard time window by using both genetic algorithm and heuristic. A mathematical programming model was also suggested in the study. The suggested mathematical programming model gives an optimal solution by using ILOG-CPLEX. This study also suggests a hybrid genetic algorithm which considers the improvement of generation for an initial solution by savings heuristic and two heuristic processes. Two heuristic processes consists of 2-opt and Or-opt. Hybrid genetic algorithm is also compared with existing problems suggested by Solomon. We found better solutions rather than the existing genetic algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.238-245
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• 2023

As technologies have been more quickly developed in this 4th Industry Revolution era, their application to defense industry has been also growing. With these much advanced technologies, we attempt to use Manned-Unmanned Teaming systems in various military operations. In this study, we consider the Location-Routing Problem for reconnaissance surveillance missions of the maritime manned-unmanned surface vehicles. As a solution technique, the two-phase method is presented. In the first location phase, the p-median problem is solved to determine which nodes are used as the seeds for the manned vehicles using Lagrangian relaxation with the subgradient method. In the second routing phase, using the results obtained from the location phase, the Vehicle Routing Problems are solved to determine the search routes of the unmanned vehicles by applying the Location Based Heuristic. For three network data sets, computational experiments are conducted to show the performance of the proposed two-phase method.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.382-392
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• 2006

Vendor-managed inventory policy(VMIP) is a supply-chain initiative where the supplier is authorized to manage inventories of items at retail locations. In VMIP, the supplier monitors sales and stock information at retail locations and makes decisions of inventory replenishment and transportation simultaneously. VMIP has been known as an effective supply chain strategy that can realize many of benefits obtainable only in a fully integrated supply chain. However, VMIP does not always lead to lower the supply chain cost. It sometimes generates the total supply chain cost higher than the traditional retailer-managed inventory policy (RMIP). In this paper, we perform a comparison study on RMIP and VMIP in the retail supply chain which consists of a single supplier and a number of retailers. We formulate mixed integer programming models for both RMIP and VMIP with vehicle routing problems and perform computational experiments on various test problems. Furthermore, we derive the conditions which guarantee the dominant position for VMIP with respect to total supply chain cost in the simple retail supply chain.

• Journal of Navigation and Port Research
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• v.30 no.9
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• pp.773-777
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• 2006

Significant increase of container flows in the marine terminals requires more efficient port equipments such as logistic and transfer systems. This paper presents collision avoidance and routing approach based on dynamic programming (DP) algorithm for a linear motor based shuttle car which is considered as a new transfer system in the port terminals. Most of routing problems are focused on automatic guided vehicle (AGV) systems, but its solutions are hardly utilized for LM based shuttle cars since both are mechanically different. Our proposed DP is implemented for real-time searching of an optimal path for each shuttle car in the Agile port terminal located at California in USA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3100-3116
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• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.