• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.7-14
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• 2016

Unlike most researches that focus on single manufacturer or single buyer, this research studies the cooperation policy for two participants of supply chain such as single vendor and single buyer. Especially, this paper deals with single vendor-single buyer integrated-production inventory problem. If the buyer orders products, then the vendor will start to make products and then the products will be shipped from the vendor to the buyer many times. The buyer is supposed to order again when the buyer's inventory level hits reorder point during the last shipment and this cycle keeps repeated. The buyer uses continuous review inventory policy and customer's demand is assumed to be probabilistic. The contribution of this paper is to present a mixed approach and derive its cost function. The existing policy assumes that the size of shipping batch from single vendor to single buyer is increasing, called Type 1, or constant, called Type 2. In mixed approach, the size of shipping batch is increasing at the beginning part of the cycle, and then its size is constant at the ending part of the cycle. The number of shipping for Type 1 and Type 2 in a cycle in mixed approach is determined to minimize total cost. The relationship between parameters, for example, the holding cost per product, the set up cost per order, and the shortage cost per item and decision variables such as order quantity, safety factor, the number of shipments, and shipment increasing factor is figured out via sensitivity analysis. Finally, it is statistically proved that the mixed approach is superior to the existing approaches.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.19-27
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• 2016

Maritime transport is now regarded as one of the main contributors to global climate change by virtue of its $CO_2$ emissions. Meanwhile, slow steaming, i.e., slower ship speed, has become a common practice in the maritime industry so as to lower $CO_2$ emissions and reduce bunker fuel consumption. The practice raised various operational decision issues in terms of shipping companies: how much ship speed is, how much to bunker the fuel, and at which port to bunker. In this context, this study addresses an operation problem in a shipping companies, which is the problem of determining the ship speed, bunkering ports, and bunkering amount at the ports over a given ship route to minimize the bunker fuel and ship time costs as well as the carbon tax which is a regulatory measure aiming at reducing $CO_2$ emissions. The ship time cost is included in the problem because slow steaming increases transit times, which implies increased in-transit inventory costs in terms of shippers. We formulate the problem as a nonlinear lot-sizing model and suggest a Lagrangian heuristic to solve the problem. The performance of the heuristic algorithm is evaluated using the data obtained from reliable sources. Although the problem is an operational problem, the heuristic algorithm is used to address various strategic issues facing shipping companies, including the effects of bunker prices, carbon taxes, and ship time costs on the ship speed, bunkering amount and number of bunkering ports. For this, we conduct sensitivity analyses of these factors and finally discuss study findings.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.106-119
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• 2023

Due to global decarbonization movement and tightening of maritime emissions restrictions, the shipping industry is going to switch to alternative fuels. Among candidates of alternative fuel, methanol is promising for decreasing SOx and CO2 emissions, resulting in minimum climate change and meeting the goal of green shipping. In this study, a novel combined system of direct methanol solid oxide fuel cells (SOFC), proton exchange membrane fuel cells (PEMFC), gas turbine (GT), and organic Rankine cycle (ORC) targeted for marine vessels was proposed. The SOFC is the main power generator of the system, whereas the GT and PEMFC could recover waste heat from the SOFC to generate useful power and increase waste heat utilizing efficiency of the system. Thermodynamics model of the combined system and each component were established and analyzed. Energy and exergy efficiencies of subsystems and the entire system were estimated with participation of the first and second laws of thermodynamics. The energy and exergy efficiencies of the overall multigeneration system were estimated to be 76.2% and 30.3%, respectively. The combination of GT and PEMFC increased the energy efficiency by 18.91% compared to the SOFC stand-alone system. By changing the methanol distribution ratio from 0.05 to 0.4, energy and exergy efficiencies decreased by 15.49% and 5.41%, respectively. During the starting up and maneuvering period of vessels, a quick response from the power supply system and propulsion plant is necessary. Utilization of PEMFC coupled with SOFC has remarkable meaning and benefits.

• Journal of Navigation and Port Research
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• v.33 no.7
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• pp.491-500
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• 2009

In order to attract more transshipment cargoes, Busan Port Authority (BPA) has, since 2003, adopted the volume incentive policy by which more than US$ 10 million annually have been paid back to shipping lines that were called at the port. However, having been a transshipment port for the Northeast region of China, the port of Busan has come under threat from bold Chinese port development projects, notably Shanghai, as northern Chinese regionnl ports place more emphasis on building facilities capable of handling growing trade volumes. Undoubtedly this would lead to a decline in transshipment container traffic moved via Busan. The purpose of this paper is to identify some core factors that have been affecting the increase of transshipment cargoes of Busan and further to recommend BPA an improved incentive scheme with which more T/S cargoes can be attracted into the port of Busan To clarity the reason why T/S cargoes have increased in the port of Busan, several steps are made as follows: The first step is to make a quantitative model for explaining the development of T/S cargoes during the last decade. The second step is to define the dependent and the independent variables for multiple regressions after testing variable significance. For this, data collection and the accuracy of validation have been done by the direct interview with the experienced staffs in shipping companies of both domestic and foreign country. After validating the model with collected data, the final step is to find variables which are explaining the model mostly. In conclusion, 2 variables were clearly identified as core factors that explain well the development of T/S cargoes in the port of Busan: 'Mohring effect' and total cost. It is strongly recommended, by an empirical study, that an incentive scheme be changed to a way which more feeder vessels rather than mother vessels can reduce their direct costs to call in the port of Busan.

• Journal of Korea Port Economic Association
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• v.30 no.1
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• pp.143-157
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• 2014

Most metropolitan shippers (MS) have used trans pacific route (TPR) or Asia-Europe route (AEP) through Busan port (BP). If Incheon new port (INP) sets up the deep water-depths under -16m, however, there might be a change in MS's port choice behavior (PCB). In this respect, the aim of this paper is to estimate an INP's allotment rate for metropolitan cargo using Logit Model (LM) considering changing global shipping and port environment. This paper reviews previous studies related to shippers' PCB then sets up the utility function (UF) including the dummied dependent variable which is comprised of BP and INP, and some independent variables such as the frequency of liner shipping route (TPR), inland transportation fare, and the rate of container terminal service. As a result of LM analysis, BP has 0.6618 and INP has 0,3382.

• Journal of Ocean Engineering and Technology
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• v.33 no.1
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• pp.33-41
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• 2019

Estimating fatigue damage is a very important issue in the design of ships. The springing and whipping response, which is the hydro-elastic response of the ship, can increase the fatigue damage of the ship. So, these phenomena should be considered in the design stage. However, the current studies on the the application of springing and whipping responses at the design stage are not sufficient. So, in this study, a prediction method was developed using fluid-structural interaction analysis to assess of the fatigue damage induced by springing and whipping. The stress transfer function (Stress RAO) was obtained by using the 3D FE model in the frequency domain, and the fatigue damage, including linear springing, was estimated by using the wide band damage model. We also used the 1D beam model to develop a method to estimate the fatigue damage, including nonlinear springing and whipping by the vertical bending moment in the short-term sea state. This method can be applied to structural members where fatigue strength is weak to vertical bending moments, such as longitudinal stiffeners. The methodology we developed was applied to 325K VLOC, and we analyzed the effect of the springing and whipping phenomena on the existing design.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.153-164
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• 2022

In this study, we estimate the quantile-regression framework of the shipping industry for the Capesize used ship, which is a typical raw material transportation from January 2000 to December 2021. This research aims two main contributions. First, we analyze the relationship between the Capesize used ship, which is a typical type in the raw material transportation market, and the freight market, for which mixed empirical analysis results are presented. Second, we present an empirical analysis model that considers the structural transformation proposed in the Hyunsok Kim and Myung-hee Chang(2020a) study in quantile-regression. In structural change investigations, the empirical results confirm that the quantile model is able to overcome the problems caused by non-stationarity in time series analysis. Then, the long-run relationship of the co-integration framework divided into long and short-run effects of exogenous variables, and this is extended to a prediction model subdivided by quantile. The results are the basis for extending the analysis based on the shipping theory to artificial intelligence and machine learning approaches.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.58-72
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• 2009

The main activities of container terminals are to load container freights to vessels, discharge them from vessels, and store them in the storage yard. Container terminals make many operational plans to execute these functions effectively. If the plans do not consider enough the loads of related resources, they may have low actualities. This study discusses the optimal yard planning model which considers various resources, such as the storage yard, yard cranes, internal vehicles, and travel lanes, in container terminals. The model determines the groups and amounts of containers which are stored in each storage block by using the resource profile. The yard planning problem is represented to the multi-commodity minimal cost flow problem and is formulated to the linear programming model. In order to explain the application of the mathematical model, the numerical examples are presented. Additionally, the relationship between the average load ratio and the relocation ratio is discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.39-50
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• 1988

The warehousing of inventories is an enormous expense to industries worldwide, and yet there are few available that can be used to design rack storage systems while considering overall system costs. The primary objective of this paper is the development of an overall ware hous storage system costs model to aid a warehous planner in the design of automated warehouse systems. A simulation model and statistical estimation procedures are used to determine the maximum inventory levels accumulated in the receiving, storage, and shipping areas. The overall cost model is developed to determine the required total land, the initial investment fund, the number of pieces of handling equipment, and the storage rack configuration for the main storage area. A numerical example is then presented to demonstrate the application of the overall system cost model developed in this paper.