• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.162-163
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• 2016

This paper presents a mathematical model for optimizing earthwork allocation plan that minimizes earthwork cost. The model takes into account operational constraints in the real-world earthwork such as material-type (i.e., quality level of material) and quantities excavated from cut-sections, required quality of material and quantities for each embankment layer, top-down cutting and bottom-up filling constraints, and allocation orders. These constraints are successfully handled by assuming the rock-earth material as the three dimensional (3D) blocks. The study is of value to project scheduler because the model identifies the optimal earth allocation plan (i.e., haul direction (cut and fill pairs), quantities of soil, type of material, and order of allocations) expeditiously and is developed as an automated system for usability. It is also relevant to estimator in that it computes more realistic earthworks costs estimation. The economic impact and validity of the mathematical model was confirmed by performing test cases.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.35-44
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• 2003

Recovery of end-of-life (EOL) products is an environmentally and economically sound way to achieve many of the goals of sustainable development. Many product recovery systems are dependent upon destructive disassembly such as shredding, which undesirably causes a large volume of shredder dust and makes parts reuse impossible. Although non-destructive disassembly has been considered as an alternative for solving the problems, the classification of disassembled items has not been sufficiently investigated. In this paper, we propose a model that mathematically optimizes the disassembly and classification of EOL products. Based on the AND/OR graph that illustrates all possible disassembly sequences of a given product, we identify the physical properties that are considered as constraints in the model. As a result of the solution procedure, the recovery problem can be transformed into a mixed integer linear programming (MILP) model. We show an example that illustrates the concept of our model.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.155-164
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• 2012

As the global market becomes more competitive, manufacturing industries face relentless pressure caused by a growing tendency of greater varieties of products, shorter manufacturing cycles and more sophisticated customer requirements. Efficient and effective supplier selection and order allocation decisions are, therefore, important decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular, when customers are willing to accept products with less desirable product attributes (e.g., color, delivery date) for economic reasons. This paper attempts to solve optimally the challenging problem of supplier selection and order allocation, taking into consideration the customer flexibility for a manufacturer producing multi-products to satisfy the customers' demands in a multi period planning horizon. A new mixed integer programming model is developed to describe the behavior of the supply chain. The objective is to maximize the manufacturer's total profit subject to various operating constraints of the supply chain. Due to the complexity and non-deterministic polynomial-time (NP)-hard nature of the problem, an improved genetic approach is proposed to solve the problem optimally. This approach differs from a canonical genetic algorithm in three aspects: a new selection method to reduce the chance of premature convergence and two problem-specific repair heuristics to guarantee feasibility of the solutions. The results of applying the proposed approach to solve a set of randomly generated test problems clearly demonstrate its excellent performance. When compared with applying the canonical genetic algorithm to locate optimal solutions, the average improvement in the solution quality amounts to as high as ten percent.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.2
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• pp.16-26
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• 2010

The transmission valuation methodology we propose here captures the interaction between generation and transmission investment decisions recognizing that a transmission expansion can impact the profitability of new resources investment, so that a methodology should consider both the objectives of investors in resources and the transmission planner. In this perspective, this paper purports to develop the mixed-integer programming based transmission expansion planning optimization software, which is well designed to determine the construction time and place of new generators, transmission lines, and substations as well as their capacities to minimize total expenditures related to their investment and operations while meeting technical constraints such as capacity margin, constitution ratio of power resources, spinning reserves, energy and fuel constraints, transmission line outages and losses, pi-type branching, and so on. Finally, Garver's simple system is adopted to validate not simply the accuracy but the efficiency of the proposed model in this paper.

• Journal of Navigation and Port Research
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• v.30 no.6 s.112
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• pp.457-464
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• 2006

Remarshalling operation is one of the operations considered important in an automated container terminal to perform quickly loading operations and delivery operations. It arranges the containers scattered at a verticla yard block in order to reduce the transfer time and the rehandling time of ATC(Automated Transfer Crane)s. This paper deals with the remarshalling planning problem minimizing the weighted operation time. This problem can be decomposed into 2 subproblems, storage space assignment problem and operation sequencing problem Storage space assignment problem decides to where containers are transported in terms of transportation time cost.. With results of a previous subproblem, operation sequence problem determines the ATC operation sequence, which minimizes the dead-heading of ATC This study formulates each subproblem with mixed integer program and dynamic program. To illustrate the proposed model, we propose an instance to explain the process of remarshalling planning.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.149-154
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• 2017

Recently, container terminal operators have made efforts to develop an efficient remarshalling plan in response to the increase in automation of equipment handling and transport of containers in the terminals. Usually, containers are handled by multiple AYCs(automated yard cranes) in-yard in an automated container terminal, and terminal operators establish a remarshalling plan using slack time to increase the efficiency of ship operation. This study develops the optimal mathematical model through mixed integer programming as a solution to the problem of dispatching multiple AYCs. Considering the difficulty of direct application to the field due to computation time, we analyze the five prototypical dispatching rules for real world adaptation. A numerical experiment found that the maximum weight ratio (MR) rule and the maximum weight (MW) rule are the ideal dispatching solutions to the multiple AYCs dispatching problem.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.143-150
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• 2014

Cloud computing is fast becoming the wave of the future for both home and business computing. Because of this growing acceptance, we can expect an explosion of diverse cloud service providers in the coming years. However, the cloud is not a single entity, rather it is a set of many disconnected islands of application (SaaS), infrastructure (IaaS), and different platform (PaaS) services. Cloud brokering mechanisms are essential to transform the heterogeneous cloud market into a commodity-like service. Cloud service brokers (CSBs) are the new form of business entities to help to aggregate the scattered set of cloud services and make conveniently available to their diverse users. CSBs can reserve a certain percentage of their clients' (users') demand and satisfy the remaining portion in an on-demand basis. In doing so, they need to minimize cost of both reserved and on-demand instances as well as the distance of a link between the cloud service provider (CSP) and the user. The study proposes a reservation approach with a mixed integer model to optimizes the cloud service cost and quality.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.219-226
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• 2020

The container terminal operators established a re-marshalling plan to reduce the loading operation time and the release operation time. Re-marshalling is to rearrange the containers in the container yard to the advantageous position to shorten the working time using the spare time of the automated yard crane. This study assumed the automated container terminal with a perpendicular layout and deals with the inter-bay re-marshalling planning problem in a yard block. The inter-bay re-marshalling plan determines the container to be moved, the location to be relocated, and the sequence of relocation operations. This study presents a mixed integer programming model that simultaneously determines the storage location and the operation sequence while satisfying the spatial availability during the re-marshalling. Numerical experiments are conducted to understand re-marshalling operation using a beam search method.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.67-78
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• 2021

The number of domestic e-commerce transactions has been breaking its own record by an annual average growth rate of over 20% based on volume for the past 5 years. Due to the rapid increase in e-commerce market, retail companies that have difficulty meeting consumers in person are in fierce competition to take the lead in the last mile service, which is the only point of contact with customers. Especially in the delivery area, where competition is most intense, the role of the fulfillment center is very important for service differentiation. It must be capable of fast product preparation ordered by consumers in accordance with the delivery service level. This study focuses on the order picking system for rapid order processing in the fulfillment center as an alternative for companies to gain competitive advantage in the e-commerce market. A mixed integer programming model was developed and implemented to optimize the stock replenishment in order picking facilities. The effectiveness was scientifically and objectively verified by simulation using the actual operation process and data.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.65-78
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• 2013

Circular shareholding is established when at least three member firms in a business group hold stock in other member firms and form a series of ownership in a circular way. Although there have been many studies which investigated a negative effect of circular shareholding on firm's value, few studies have discussed how to resolve the problem given complicated ownership structures of large business groups. This paper is based on a mixed integer programming model, which was proposed in the author's previous research and can identify the ownership share divested in order to resolve circular shareholding. Since the optimization model becomes too complicated for large business groups and requires a sophisticated software to solve it, we propose a simple heuristic method that can find a good approximate solution to the model. Its applications to twelve Korean large business groups show that the heuristic method is not just computationally attractive but also provides near-optimal solutions in most cases.