• Journal of the Korean Operations Research and Management Science Society
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• v.9 no.2
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• pp.3-8
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• 1984

This paper considers the intermediate warehouse location problem in a two stage distribution system where commodities are delivered from the given set of capacitated factories to customers via uncapacitated intermediate warehouses. In order to determine the subset of warehouses to open which minimizes the total distribution costs including the fixed costs associated with opening warehouses, the cross decomposition method for mixed integer programming recently developed by T.J. Van Roy is used. The cross decomposition unifies Benders decomposition and Lagrangean relaxation into a single framework that involves successive solutions to a primal subproblem and a dual subproblem. In our problem model, primal subproblem turns out to be a transshipment problem and dual subproblem turns out to be an intermediate warehouse location problem with uncapacitated factories.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.125-135
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• 1993

An Unrelated Parallel Processing with Weighted jobs and Setup times scheduling prolem is studied. We consider a parallel processing in which a group of processors(machines) perform a single operation on jobs of a number of different job types. The processing time of each job depends on both the job and the machine, and each job has a weight. In addition each machine requires significant setup time between processing jobs of different job types. The performance measure is to minimize total weighted flow time in order to meet the job importance and to minimize in-process inventory. We present a 0-1 Mixed Integer Programming model as an optimizing algorithm. We also present a simple heuristic algorithm. Computational results for the optimal and the heuristic algorithm are reported and the results show that the simple heuristic is quite effective and efficient.

• IE interfaces
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• v.20 no.1
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• pp.33-40
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• 2007

In this paper, we consider a scheduling problem of shipyard sub-assembly process. We introduce a skid conveyor system in a shipbuilding company. We develop a mathematical model and a genetic algorithm for shipyard sub-assembly process. The objective of the scheduling is to minimize the makespan which is the final completion time of all jobs. Numerical experiments show that the genetic algorithm performs efficiently.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.421-429
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• 2014

We consider the problem of scheduling communications in wireless sensor networks (WSNs) to ensure battery preservation through the use of the sleeping mode of sensors.We propose a communication protocol for 1-hop WSNs and extend it to multi-hop WSNs through the use of a 1-hop clustering algorithm.We propose to schedule communications in each cluster in a virtual communication ring so as to avoid collisions. Since clusters are cliques, only one sensor can speak or listen in a cluster at a time, and all sensors need to speak in each of their clusters at least once to realize the communication protocol. We model this situation as a mathematical program.

• Annual Conference of KIPS
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• 2016.04a
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• pp.464-465
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• 2016

This paper analyzes the capabilities of multi-agent system (MAS) technology for the optimal multi-microgrids (MMGs) operation in grid-connected mode. In this system, communication among microgrids (MGs) is realized by developing a modified contract net protocol (MCNP) based on agent communication language (ACL) messages. Moreover, a two-stage mathematical model is proposed based on mixed integer linear programming (MILP) for local optimization in each MG, and global optimization in energy management system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.1-8
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• 2010

A vendor selection problem consists of two different kinds of decision making. First one is to choose the best suppliers among all possible suppliers and the next is to allocate the optimal quantities of orders among the selected vendors. In this study, an integration of the technique for order preference by similarity to ideal solution (TOPSIS) and a multi-objective mixed integer programming (MOMIP) is developed to account for all qualitative and quantitative factors which are used to evaluate and choose the best group of vendors and to decide the optimal order quantity for each vendor. A solution methodology for the vendor selection model of multiple-vendor, multiple-item with multiple decision criteria and in respect to finite vendor capacity is presented.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.1-8
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• 2001

Redundancy allocation problems have been considered at single-level systems and it may be the best policy in some specific situations, but not in general. With regards to reliability, it is most effective to allocate the lowest objects, because parallel-series systems are more reliable than series-parallel systems. However, the smaller and lower in the system an object is, the more time and accuracy are needed for duplicating it, and so, the cost can be decreased by using modular redundancy Therefore, providing redundancy at high levels like as modules or subsystems, can be more economical than providing redundancy at low levels or duplicating components. In this paper, the problem in which redundancy is allocated at all level in a series system is addressed, a mixed integer nonlinear programming model is presented and a genetic algorithm is proposed. An example illustrates the procedure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.192-202
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• 2009

Disassembly of products at their end-of-life (EOL) is a prerequisite for recycling or remanufacturing, since most products should be disassembled before being recycled or remanufactured as secondary parts or materials. In disassembly sequence planning of EOL products, considered are the uncertainty issues, i.e., defective parts or joints in an incoming product, disassembly damage, and imprecise net profits and costs. The paper deals with the problem of determining the disassembly level and corresponding sequence, with the objective of maximizing the overall profit under uncertainties in disassembly cost and/or revenue. The solution is represented as the longest path on a directed acyclic graph where parameter (arc length) uncertainties are modeled in the form of intervals. And, a heuristic algorithm is developed to find a path with the minimum worst case regret, since the problem is NP-hard. Computational experiments are carried out to show the performance of the proposed algorithm compared with the mixed integer programming model and Conde's heuristic algorithm.

• ETRI Journal
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• v.41 no.2
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• pp.207-223
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• 2019

Network function virtualization can significantly improve the flexibility and effectiveness of network appliances via a mapping process called service function chaining. However, the failure of any single virtualized network function causes the breakdown of the entire chain, which results in resource wastage, delays, and significant data loss. Redundancy can be used to protect network appliances; however, when failures occur, it may significantly degrade network efficiency. In addition, it is difficult to efficiently map the primary and backups to optimize the management cost and service reliability without violating the capacity, delay, and reliability constraints, which is referred to as the reliability-aware service chaining mapping problem. In this paper, a mixed integer linear programming formulation is provided to address this problem along with a novel online algorithm that adopts the joint protection redundancy model and novel backup selection scheme. The results show that the proposed algorithm can significantly improve the request acceptance ratio and reduce the consumption of physical resources compared to existing backup algorithms.

• Journal of Korean Society for Quality Management
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• v.16 no.1
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• pp.78-87
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• 1988

The purpose of this study is to develop the algorithm applicable to the integrated production inventory model under quantity discount. To achieve this purpose, the integrated production inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system is considered. The product is manufactured in batches and the raw materials are obtained from outside suppliers but some of the raw materials are discounted according to the purchasing quantity. The intergrated production inventory problem considered in this study is formulated by the non-linear mixed integer programming model, and the optimal solution is obtained by using the algorithm developed by Goyal. Then, the algorithm developed by this study is applied to the quantity discount problem, and the optimal solution is revised by this results. The quantity discount algorithm of the integrated production inventory model developed by this study gives a systematic procedure to obtain the optimum policy to minimize the total cost in any case. The numerical example involving 20 raw materials and 5 raw materials among them are discounted according to the purchasing quantity is given to verify the mathematical model and the algorithm developed in this study.