• IE interfaces
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• v.16 no.4
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• pp.441-449
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• 2003

In this paper we propose a distribution planning method aiming the use in the real-life situations. The assumed form of the distribution network is arborescence. At every node in the distribution network, orders are placed periodically. At each renewal of planning horizon, demand informations of periods in the horizon are updated. The objective of the problem is to minimize the total cost, which is the sum of holding and backorder costs of all sites during planning horizon. For such a situation, this study addressed an effective distribution plan when demands for demand-sites are provided for a given planning horizon.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.135-150
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• 2002

The basic assumption of analytical Dynamic Traffic Assignment models is that traffic demand and network conditions are known as a priori and unchanging during the whole planning horizon. This assumption may not be realistic in the practical traffic situation because traffic demand and network conditions nay vary from time to time. The rolling horizon implementation recognizes a fact : The Prediction of origin-destination(OD) matrices and network conditions is usually more accurate in a short period of time, while further into the whole horizon there exists a substantial uncertainty. In the rolling horizon implementation, therefore, rather than assuming time-dependent OD matrices and network conditions are known at the beginning of the horizon, it is assumed that the deterministic information of OD and traffic conditions for a short period are possessed, whereas information beyond this short period will not be available until the time rolls forward. This paper introduces rolling horizon implementation to enable a multi-class analytical DTA model to respond operationally to dynamic variations of both traffic demand and network conditions. In the paper, implementation procedure is discussed in detail, and practical solutions for some raised issues of 1) unfinished trips and 2) rerouting strategy of these trips, are proposed. Computational examples and results are presented and analyzed.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.67-74
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• 1989

This paper considers single-product production and inventory management problem where cumulative demands up to each time period are mutually independent random variables(known) having continuous probability distributions and the associated cost-minimizing production schedule (when to produce and how much to produce) need be determined in rolling horizon environment. For the problem, both the production cost and the inventory holding and backlogging costs are included in the whole system cost. The probability distributions of these costs are expressed in terms of random demands, and utilized to exploit a solution procedure for a production schedule which minimizes the expected unit time system cost and also reduces the probability of rist that, for the first-period of each production cycle (rolling horizon), the cost of the "production" option will exceed that of the "non-production" one. Numerical examples are presented for the solution procedure illustration.cedure illustration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1838-1855
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• 2008

The manufacturing industry seeks for improvements in efficiency at the manufacturing process. This paper presents a method for effective real time dispatching for parallel machines with multi product that minimizes mean tardiness and maximizes the quality of the product. What is shown in this paper is that using the Rolling Horizon Tabu search method in the real time dispatching process, mean tardiness can be reduced to the minimum. The effectiveness of the method presented in this paper has been examined in the simulation and compared with other dispatching methods. In fact, using this method manufacturing companies can increase profits and improve customer satisfaction as well.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2236-2244
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• 2018

We make optimal consecutive offer curves for an energy storage system (ESS) integrated wind power producer (WPP) in the co-optimized day-ahead energy and regulation markets. We build the offer curves by solving multi-stage stochastic optimization (MSSO) problems based on the scenarios of pairs consisting of real-time price and wind power forecasts through the progressive hedging method (PHM). We also use the rolling horizon method (RHM) to build the consecutive offer curves for several hours in chronological order. We test the profitability of the offer curves by using the data sampled from the Iberian Peninsula. We show that the offer curves obtained by solving MSSO problems with the PHM and RHM have a higher profitability than offer curves obtained by solving deterministic problems.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.4
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• pp.398-408
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• 2016

Based on non-completely hybrid flow line scheduling of panel block in shipbuilding, several uncertain factors influencing the problem were analyzed in a real environment, and a nonlinear integer programming model was built for each sub-scheduling problem. To narrow the difference between theory and application, rolling horizon and rescheduling methods are proposed. Moreover, with respect to the uncertainty of processing time, arriving time and due time, we take the minimizing of the early and delayed delivery costs as the objective, and establish an evaluation with a global penalty function. Finally, numerical experiments and a simulation analysis were undertaken to demonstrate the effectiveness of the model and algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.932-938
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• 2017

This paper presents the structure of an energy management system for distributed energy resources of a grid-connected microgrid. The energy management system of a grid-connected microgrid collects information of the microgrid such as the status of distributed energy resources and the time varying pricing plan through various protocols. The energy management system performs forecasting and optimization based on the collected information. It derives the operation schedule of distributed energy resources to reduce the microgrid electricity bill. In order to achieve optimal operation, the energy management system should include an optimal scheduling algorithm and a protocol that transfers the derived schedule to distributed energy resources. The energy management system operates as a rolling horizon controller in order to reduce the effect of a prediction error. Derived control schedules are transmitted to the distributed energy resources in real time through the international standard communication protocol.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.233-241
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• 2003

The rolling schedule procedure has been an important part of the Enterprise Resource Planning (ERP) systems. The performance of production planning in an ERP system depends on the selection of the three parameters in rolling schedule procedure: frozen interval, replanning interval, and planning horizon (forecast window). This research investigated, in a theoretical approach, the combined impact of selections of those three parameters. The proven mathematical theorems provided guidance to re-duction of instability (nervousness) and to seek the optimal balance between stability and responsiveness of ERP systems. Further the theorems are extended to incorporate the cost structure.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1258-1263
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• 2011

This study was conducted to reclassify Asan series based on the second edition of Soil Taxonomy and to discuss the formation of Asan series distributed on the rolling to hilly areas. Morphological properties of typifying pedon of Asan series were investigated and physico-chemical properties were analyzed according to Soil survey laboratory methods manual. The typifying pedon of Asan series has dark yellowish brown (10YR 4/4) gravelly loam Ap horizon (0-18 cm), strong brown (7.5YR 5/6) gravelly clay loam BA horizon (18-30 cm), red (2.5YR 4/6) gravelly clay loam Bt1 horizon (30-52 cm), red (2.5YR 4/8) gravelly clay loam Bt2 horizon (52-98 cm), and red (2.5YR 4/8) gravelly clay loam C horizon (98-160 cm). The typifying pedon has an argillic horizon from a depth of 30 to 98 cm and a base saturation (sum of cations) of less than 35% at 125 cm below the upper boundary of the argillic horizon. It can be classified as Ultisol, not as Inceptisol. It has udic soil moisture regime, and can be classified as Udult. Also that meets the requirements of Typic Hapludults. It has 18-35% clay at the particle-size control section, and has mesic soil temperature regime. Therefore Asan series can be classified as fine loamy, mesic family of Typic Hapludults, not as fine loamy, mesic family of Typic Dystrudepts. Asan series occur on rolling to hilly areas in residual materials derived from granite gneiss, schist, and gneiss rocks. They are developed as Ultisols with clay mineral weathering, translocation of clays to accumulate in an argillic horizon, and leaching of base-forming cations from the profile for relatively long periods under humid and temperate climates in Korea.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.57-65
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• 2008

Available-to-promise (ATP) exhibiting availability of manufacturing resources can be used to support customer order promising. Recently, one advanced function called Capable-to-promise (CTP) is provided by several modern APS (advanced planning system) that checks available capacity for placing new production orders or increasing already scheduled production orders. At the customer enquiry stage while considering the order delivery date and quantity to quote, both ATP and CTP are allocated to support order promising. In particular, current trends of mass customization and multi-side production chain derive several new constraints that should be considered when ATP/CTP allocation planning for order promising - such as customer's preference plants or material vendors, material compatibility, etc. Moreover, ATP/CTP allocation planning would be executed over a rolling time horizon. To utilize capacity and material manufacturing resource flexibly and fulfill more customer orders, ATP/CTP rolling planning should possess resource reallocation mechanism under the constraints of order quantities and delivery dates for all previous order promising. Therefore, to enhance order promising with reliability and flexibility to reallocate manufacturing resource, the ATP/CTP reallocation planning mechanism is needed in order to reallocate material and capacity resource for fulfilling all previous promised and new customer orders beneficially with considering new derived material and capacity constraints.