• Korean Management Science Review
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• v.32 no.1
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• pp.49-63
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• 2015

This paper investigates an aircraft-target assignment problem in consideration of deconfliction. The aircraft-target assignment problem is the problem to assign available aircrafts and weapons to targets that should be attacked, where the objective function is to minimize the total expected damage of aircrafts. Deconfliction is the way of dividing airspaces for aircraft flight to ensure the safety while performing the mission. In this paper, mixed integer programming model is suggested, where it considers deconfliction between aircrafts. However, the suggested MIP model is non-linear and limited to get solution for large size problem. The 2-phase decomposition model is suggested for efficiency and computation, where in the first phase target area is divided into sectors for deconfliction and in the second phase aircrafts and weapons are assigned to given targets for minimizing expected damage of aircraft. The proposed decomposition model shows outperforms the model developed for comparison in the computational experiment.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.398-407
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• 2014

Shortages and delays in a humanitarian logistics system can contribute to the pain and suffering of survivors or other affected people. Humanitarian logistics budgets should be sufficient to prevent such shortages or delays. Unlike commercial supply chain systems, the budgets for relief supply chain systems should be able to satisfy demand. This study describes a comprehensive model in an effort to satisfy the total relief demand by minimizing logistics operations costs. We herein propose a strategic model which determines the locations of distribution centers and the total inventory to be stocked for each distribution center where a flood or other catastrophe may occur. The proposed model is formulated and solved as a mixed-integer programming problem that integrates facility location and inventory decisions by considering capacity constraints and time restrictions in order to minimize the total cost of relief operations. The proposed model is then applied to a real flood case involving 47 disaster areas and 13 distribution centers in Thailand. Finally, we discuss the sensitivity analysis of the model and the managerial implications of this research.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.305-314
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• 2017

Most of the existing researches on systemwide optimization of generator maintenance scheduling do not consider the equivalent operating hours(EOHs) mainly due to the difficulties of calculating the EOHs of the CCGTs in the large scale system. In order to estimate the EOHs not only the operating hours but also the number of start-up/shutdown during the planning period should be estimated, which requires the mathematical model to incorporate the economic dispatch model and unit commitment model. The model is inherently modelled as a large scale mixed-integer nonlinear programming problem and the computation time increases exponentially and intractable as the system size grows. To make the problem tractable, this paper proposes an EOH calculation based on demand grouping by K-means clustering algorithm. Network congestion is also considered in order to improve the accuracy of EOH calculation. This proposed method is applied to the actual Korean electricity market and compared to other existing methods.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.127-135
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• 1999

Most existing progression bandwidth models maximize the single or multi weighted sum of bandwidths in the both directions to improve traffic mobility on an arterial, but they cannot be applied to general networks. Even though a few models formulating a looped network problem cannot be applied to networks have not loops. Also they have some defects in optimizing phase sequences. Therefore, the objective of this study is to develope a mathematical formulation of the synchronization problem for a general traffic network. The goal is achieved successfully by introducing the signal phasing for each movement and expanding the mixed integer linear programming of MAXBAND. The experiments indicate that the proposed model can formulate the general traffic network problem mere efficiently than any other model. In conclusion, this model may optimize signal time to smooth progression in the general networks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.160-172
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• 2023

In contemporary global warfare, the significance and imperative of air transportation have been steadily growing. The Republic of Korea Air Force currently operates only light and medium-sized military cargo planes, but does not have a heavy one. The current air transportation capability is limited to meet various present and future air transport needs due to lack of performance such as payload, range, cruise speed and altitude. The problem of population cliffs and lack of airplane parking space must also be addressed. These problems can be solved through the introduction of heavy cargo planes. Until now, most studies on the need of heavy cargo plane and increasing air transport capability have focused on the necessity. Some of them suggested specific quantity and model but have not provided scientific evidence. In this study, the appropriate ratio of heavy cargo plane suitable for the Korea's national power was calculated using principal component analysis and cluster analysis. In addition, an optimization model was established to maximize air transport capability considering realistic constraints. Finally we analyze the results of optimization model and compare two alternatives for force structure.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.49-59
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• 2011

A ship scheduling model is presented for the raw material transportation problem with yard storage constraints in a steel mill. The problem is formulated as 0, 1 mixed integer programming considering such constraints as loading port conditions, ship size and hold capacity, unloading conditions, and yard storage space. In addition, inventory related constraints including safety stock are taken into consideration to support the continuous operations of steel making process. The proposed model has been implemented and applied successfully to a real world problem, and its results show the improvement of performance compared to the traditional method. For example, the arrival dates of ships are determined satisfying the constraints. The total inventory level is minimized at the stock yard as a result. Also, the safety inventory level is always kept at the planning stage, and the standard deviation of total inventory level is reduced significantly. Further research is expected to develop efficient heuristics to have a better response time for even larger scale problems.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.111-122
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• 1999

A service network design model for LTL freight transportation is formulated as a mixed integer Programming Problem with two heuristic solution a1gorithms. The Proposed model derives the transportation Path for each origination-destination pair, taking into account transportation cost over the links and handling costs over the nodes. The first algorithm searches for a local minimum solution from a given initial solution by improving the quality of solution repeatedly while the second a1gorithm searches for a better solution using Simulated Annealing Method. For both solution algorithms, the initial solution is derived by a modified reverse Diikstras shortest Path a1gorithm. An illustrative example, Presented in the last part of the Paper, shows that the proposed algorithms find solutions which reduce the cost by 12% and 15% respectively, compared to the initial solution.

• Korean Management Science Review
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• v.25 no.1
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• pp.107-121
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• 2008

As to more efficiently manage the inventory in the retail supply chain and to meet the customer demand in a timely manner, vendor-managed inventory (VMI) has been widely accepted, which manages inventory in the retail supply chain via sharing information and collaborating with the retailers. Applying VMI generates vendor-managed inventory/distribution problem (VMIDP), which involves inventory management for both the vendor and the retailers, and the design of vehicle routes for delivery, to minimize the total operating cost in the supply chain. In this paper, we suggest a mixed integer programming (MIP) model to obtain the optimal solution for VMIDP in a two-echelon retail supply chain, and develop an efficient heuristic based on the operating principles of the MIP model. To evaluate the performance of the heuristic, its solution was compared with the one of the MIP model on a total of twenty seven test problems. As a result, the heuristic found optimal solutions on seven problems in a significantly reduced time, and generated a 4.3% error rate of total cost in average for all problems. The heuristic is applied to the case problem of the local famous franchise company together with GIS, showing that it is capable of providing a solution efficiently in a relatively short time even in the real world situation.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.314-314
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• 1996

We investigate the scheduling problem for periodic job shops with blocking. We develop Petri net models for periodic job shops with finite buffers. A buffer control method would allow the jobs to enter the input buffer of the next machine in the order for which they are completed. We discuss difficulties in using such a random order buffer control method and random access buffers. We thus propose an alternative buffer control policy that restricts the jobs to enter the input buffer of the next machine in a predetermined order. The buffer control method simplifies job flows and control systems. Further, it requires only a cost-effective simple sequential buffer. We show that the periodic scheduling model with finite buffers using the buffer control policy can be transformed into an equivalent periodic scheduling model with no buffer, which is modeled as a timed marked graph. We characterize the structural properties for deadlock detection. Finally, we develop a mixed integer programming model for the no buffer problem that finds a deadlock-free optimal sequence that minimizes the cycle time.